Studies Related to the Involvement of EsA in Improving Intestinal Inflammation in Acute Pancreatitis via the NF-κB Pathway.

Background: Acute pancreatitis (AP) is a clinically frequent acute abdominal condition, which refers to an inflammatory response syndrome of edema, bleeding, and even necrosis caused by abnormal activation of the pancreas's own digestive enzymes. Intestinal damage can occur early in the course of AP and is manifested by impaired intestinal mucosal barrier function, and inflammatory reactions of the intestinal mucosa, among other factors. It can cause translocation of intestinal bacteria and endotoxins, further aggravating the condition of AP. Therefore, actively protecting the intestinal mucosal barrier, controlling the progression of intestinal inflammation, and improving intestinal dynamics in the early stages of AP play an important role in enhancing the prognosis of AP. Methods: The viability and apoptosis of RAW264.7 cells treated with Esculentoside A (EsA) and/or lipopolysaccharide were detected using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and flow cytometry, respectively. The expression of apoptosis-related proteins and NF-κB signaling pathway-related proteins were detected by western blot (WB). An enzyme-linked immunosorbent assay was used to measure TNF-α and IL-6 secretion. Results: In vitro experiments demonstrated that EsA not only promoted the apoptosis of inflammatory cells but also reduced the secretion of TNF-α and IL-6 in a dose-dependent manner. Additionally, it inhibited the activation of the NF-κB signaling pathway by decreasing the expression of phosphorylated-p65(p-p65) and elevating the expression of IκBα. Similarly, in vivo experiments using a rat AP model showed that EsA inhibited the expression of p-p65 elevating the expression of IκBα in the intestinal tissues of the rat AP model and promoting the apoptosis of inflammatory cells in the intestinal mucosa in vivo experiments, while improving the pathological outcome of the pancreatic and intestinal tissues. Conclusion: Our results suggest that EsA can reduce intestinal inflammation in the rat AP model and that EsA may be a candidate for treating intestinal inflammation in AP and further arresting AP progression.

Polygenic risk score predicts all-cause death in East Asian patients with prior coronary artery disease.

Introduction: Coronary artery disease (CAD) is a highly heritable and multifactorial disease. Numerous genome-wide association studies (GWAS) facilitated the construction of polygenic risk scores (PRS) for predicting future incidence of CAD, however, exclusively in European populations. Furthermore, identifying CAD patients with elevated risks of all-cause death presents a critical challenge in secondary prevention, which will contribute largely to reducing the burden for public healthcare. Methods: We recruited a cohort of 1,776 Chinese CAD patients and performed medical follow-up for up to 11 years. A pruning and thresholding method was used to calculate PRS of CAD and its 14 risk factors. Their correlations with all-cause death were computed via Cox regression. Results and discussion: We found that the PRS for CAD and its seven risk factors, namely myocardial infarction, ischemic stroke, angina, heart failure, low-density lipoprotein cholesterol, total cholesterol and C-reaction protein, were significantly associated with death (P ≤ 0.05), whereas the PRS of body mass index displayed moderate association (P < 0.1). Elastic-net Cox regression with 5-fold cross-validation was used to integrate these nine PRS models into a meta score, metaPRS, which performed well in stratifying patients at different risks for death (P < 0.0001). Combining metaPRS with clinical risk factors further increased the discerning power and a 4% increase in sensitivity. The metaPRS generated from the genetic susceptibility to CAD and its risk factors can well stratify CAD patients by their risks of death. Integrating metaPRS and clinical risk factors may contribute to identifying patients at higher risk of poor prognosis.

Autoimmune alleles at the major histocompatibility locus modify melanoma susceptibility.

Autoimmunity and cancer represent two different aspects of immune dysfunction. Autoimmunity is characterized by breakdowns in immune self-tolerance, while impaired immune surveillance can allow for tumorigenesis. The class I major histocompatibility complex (MHC-I), which displays derivatives of the cellular peptidome for immune surveillance by CD8+ T cells, serves as a common genetic link between these conditions. As melanoma-specific CD8+ T cells have been shown to target melanocyte-specific peptide antigens more often than melanoma-specific antigens, we investigated whether vitiligo- and psoriasis-predisposing MHC-I alleles conferred a melanoma-protective effect. In individuals with cutaneous melanoma from both The Cancer Genome Atlas (n = 451) and an independent validation set (n = 586), MHC-I autoimmune-allele carrier status was significantly associated with a later age of melanoma diagnosis. Furthermore, MHC-I autoimmune-allele carriers were significantly associated with decreased risk of developing melanoma in the Million Veteran Program (OR = 0.962, p = 0.024). Existing melanoma polygenic risk scores (PRSs) did not predict autoimmune-allele carrier status, suggesting these alleles provide orthogonal risk-relevant information. Mechanisms of autoimmune protection were neither associated with improved melanoma-driver mutation association nor improved gene-level conserved antigen presentation relative to common alleles. However, autoimmune alleles showed higher affinity relative to common alleles for particular windows of melanocyte-conserved antigens and loss of heterozygosity of autoimmune alleles caused the greatest reduction in presentation for several conserved antigens across individuals with loss of HLA alleles. Overall, this study presents evidence that MHC-I autoimmune-risk alleles modulate melanoma risk unaccounted for by current PRSs.

Combined therapy of prednisone and mTOR inhibitor sirolimus for treating retroperitoneal fibrosis.

OBJECTIVES: Retroperitoneal fibrosis (RPF) is a rare autoimmune disease with fibrous tissue growth and inflammation in retroperitoneum. Its current treatments involve long-term uptake of glucocorticoids (e.g., prednisone) for controlling inflammation; however, side effects are common. We strived for an improved therapy for fibrosis remission while reducing side effects. METHODS: We surveyed gene-disease-drug databases and discovered that mammalian target of rapamycin (mTOR) was a key signalling protein in RPF and the mTOR inhibitor compound sirolimus affected many RPF pathways. We designed a therapy combining a gradual reduction of prednisone with a long-term, stable dosage of sirolimus. We then implemented a single-arm clinical trial and assessed the effects in eight RPF patients at 0, 12 and 48 weeks of treatment by measuring fibrous tissue mass by CT, markers of inflammation and kidney functions by lab tests, immune cell profiles by flow cytometry and plasma inflammatory proteins by Olink proteomics. RESULTS: With the combined therapy, fibrous tissue shrunk about by half, markers of acute inflammation reduced by 70% and most patients with abnormal kidney functions had them restored to normal range. Molecularly, fibrosis-related T cell subsets, including TH2, TH17 and circulating TFH cells, were reduced and tumour necrosis factor and related cytokines restored to healthy levels. No severe long-term side effects were observed. CONCLUSIONS: Our combined therapy resulted in significant fibrosis remission and an overall regression of the immune system towards healthy states, while achieving good tolerance. We concluded that this new therapy had the potential to replace the steroid monotherapy for treating RPF.

High-frequency and functional mitochondrial DNA mutations at the single-cell level.

Decline in mitochondrial function underlies aging and age-related diseases, but the role of mitochondrial DNA (mtDNA) mutations in these processes remains elusive. To investigate patterns of mtDNA mutations, it is particularly important to quantify mtDNA mutations and their associated pathogenic effects at the single-cell level. However, existing single-cell mtDNA sequencing approaches remain inefficient due to high cost and low mtDNA on-target rates. In this study, we developed a cost-effective mtDNA targeted-sequencing protocol called single-cell sequencing by targeted amplification of multiplex probes (scSTAMP) and experimentally validated its reliability. We then applied our method to assess single-cell mtDNA mutations in 768 B lymphocytes and 768 monocytes from a 76-y-old female. Across 632 B lymphocyte and 617 monocytes with medium mtDNA coverage over >100×, our results indicated that over 50% of cells carried at least one mtDNA mutation with variant allele frequencies (VAFs) over 20%, and that cells carried an average of 0.658 and 0.712 such mutation for B lymphocytes and monocytes, respectively. Surprisingly, more than 20% of the observed mutations had VAFs of over 90% in either cell population. In addition, over 60% of the mutations were in protein-coding genes, of which over 70% were nonsynonymous, and more than 50% of the nonsynonymous mutations were predicted to be highly pathogenic. Interestingly, about 80% of the observed mutations were singletons in the respective cell populations. Our results revealed mtDNA mutations with functional significance might be prevalent at advanced age, calling further investigation on age-related mtDNA mutation dynamics at the single-cell level.

Association of serum klotho levels with different-staged vascular calcification status in patients with maintenance hemodialysis.

BACKGROUND: Vascular calcification (VC) is suggested to be associated with serum klotho levels in patients with maintenance hemodialysis (MHD), whereas there is a lack of reports on the associations of VC status in whole arteries with serum klotho contents. METHODS: One hundred forty eligible patients with MHD and a total of age-and gender-matched normal controls (NCs) were recruited. We analyzed the VC statuses of large arteries and peripheral muscular arteries by calculating the sum of scores from each artery. The levels of serum klotho were determined by ELISA. In addition, the relationship between serum klotho and VC status was evaluated using correlation analysis and regression analysis. RESULTS: The VC severity in MHD patients tended to be worse in comparison with NCs. Serum klotho level in patients with MHD was lower than that in the NC subjects (​P < 0.0001), which was correlated with VC scores as reflected by correlation analysis and regression analysis. Serum klotho concentrations exhibited a dynamic decline along with increased VC status stages. Subjects with higher levels of serum klotho had a higher prevalence of cardiovascular events. CONCLUSION: Our study indicates serum klotho is strongly associated with VC status in a stage-dependent manner.

Case report: Systemic muscle involvement as the primary clinical manifestation of chronic active Epstein-Barr virus infection: A case-based review.

Chronic active Epstein-Barr virus infection (CAEBV) is common in Asian countries and characterized by recurrent or persistent infectious mononucleosis-like symptoms. Here, we describe a rare case of CAEBV-associated generalized myositis with extranodal NK/T-cell lymphoma, who initially presented with swelling and muscle soreness in the extremities and was diagnosed as polymyositis at the initial stage. CAEBV-associated generalized myositis is different from polymyositis and other types of myositis. Furthermore, it is prone to lymphoma with poor prognosis.

Trellis for efficient data and task management in the VA Million Veteran Program.

Biomedical studies have become larger in size and yielded large quantities of data, yet efficient data processing remains a challenge. Here we present Trellis, a cloud-based data and task management framework that completely automates the process from data ingestion to result presentation, while tracking data lineage, facilitating information query, and supporting fault-tolerance and scalability. Using a graph database to coordinate the state of the data processing workflows and a scalable microservice architecture to perform bioinformatics tasks, Trellis has enabled efficient variant calling on 100,000 human genomes collected in the VA Million Veteran Program.

Common and rare variant analyses combined with single-cell multiomics reveal cell-type-specific molecular mechanisms of COVID-19 severity.

The determinants of severe COVID-19 in non-elderly adults are poorly understood, which limits opportunities for early intervention and treatment. Here we present novel machine learning frameworks for identifying common and rare disease-associated genetic variation, which outperform conventional approaches. By integrating single-cell multiomics profiling of human lungs to link genetic signals to cell-type-specific functions, we have discovered and validated over 1,000 risk genes underlying severe COVID-19 across 19 cell types. Identified risk genes are overexpressed in healthy lungs but relatively downregulated in severely diseased lungs. Genetic risk for severe COVID-19, within both common and rare variants, is particularly enriched in natural killer (NK) cells, which places these immune cells upstream in the pathogenesis of severe disease. Mendelian randomization indicates that failed NKG2D-mediated activation of NK cells leads to critical illness. Network analysis further links multiple pathways associated with NK cell activation, including type-I-interferon-mediated signalling, to severe COVID-19. Our rare variant model, PULSE, enables sensitive prediction of severe disease in non-elderly patients based on whole-exome sequencing; individualized predictions are accurate independent of age and sex, and are consistent across multiple populations and cohorts. Risk stratification based on exome sequencing has the potential to facilitate post-exposure prophylaxis in at-risk individuals, potentially based around augmentation of NK cell function. Overall, our study characterizes a comprehensive genetic landscape of COVID-19 severity and provides novel insights into the molecular mechanisms of severe disease, leading to new therapeutic targets and sensitive detection of at-risk individuals.

Swarm: A federated cloud framework for large-scale variant analysis.

Genomic data analysis across multiple cloud platforms is an ongoing challenge, especially when large amounts of data are involved. Here, we present Swarm, a framework for federated computation that promotes minimal data motion and facilitates crosstalk between genomic datasets stored on various cloud platforms. We demonstrate its utility via common inquiries of genomic variants across BigQuery in the Google Cloud Platform (GCP), Athena in the Amazon Web Services (AWS), Apache Presto and MySQL. Compared to single-cloud platforms, the Swarm framework significantly reduced computational costs, run-time delays and risks of security breach and privacy violation.

Hummingbird: efficient performance prediction for executing genomic applications in the cloud.

MOTIVATION: A major drawback of executing genomic applications on cloud computing facilities is the lack of tools to predict which instance type is the most appropriate, often resulting in an over- or under- matching of resources. Determining the right configuration before actually running the applications will save money and time. Here, we introduce Hummingbird, a tool for predicting performance of computing instances with varying memory and CPU on multiple cloud platforms. RESULTS: Our experiments on three major genomic data pipelines, including GATK HaplotypeCaller, GATK Mutect2 and ENCODE ATAC-seq, showed that Hummingbird was able to address applications in command line specified in JSON format or workflow description language (WDL) format, and accurately predicted the fastest, the cheapest and the most cost-efficient compute instances in an economic manner. AVAILABILITY AND IMPLEMENTATION: Hummingbird is available as an open source tool at: https://github.com/StanfordBioinformatics/Hummingbird. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Expression and clinical significance of thrombospondin-1 and plasminogen activator inhibitor-1 in patients with mesangial proliferative glomerulonephritis.

BACKGROUND: As a common pathological type of glomerular disease in China, mesangial proliferative glomerulonephritis is related to plasminogen activator inhibitor-1 (PAI-1) and thrombospondin-1 (TSP-1). Here, this study aims to investigate the expression and clinical significance of TSP-1 and PAI-1 in patients with mesangial proliferative glomerulonephritis. METHODS: Renal tissue specimens from 46 patients with mesangial proliferative glomerulonephritis admitted to this hospital were selected as the subjects, and 8 specimens of renal tissue from autopsy were used as controls. The expression levels of TSP-1 and PAI-1 were detected by immunohistochemistry and analyzed. RESULTS: The 24-hour urine protein, triglyceride, and total cholesterol levels of patients with severe mesangial hyperplasia were significantly higher than those of patients with mild and moderate mesangial hyperplasia, and serum albumin was lower than that of patients with mild and moderate mesangial hyperplasia (P<0.05). The 24-hour urine protein level of patients with moderate mesangial hyperplasia was higher than that of patients with mild mesangial hyperplasia while the albumin level was lower (P<0.05), but there was no significant difference in triglyceride and total cholesterol (P>0.05). There was no significant difference in creatinine clearance (Ccr) between the three groups (P>0.05).The 24-hour urine protein and urine alpha-1-microglobulin (A1M) levels in patients with renal interstitial disease were higher than those in patients without renal interstitial disease, while their Ccr level was lower (P<0.05). TSP-1 and PAI-1 were not positively expressed in the glomeruli and renal tubules of specimens of the control group. However, in mesangial hyperplasia patients, the expression of TSP-1 and PAI-1 in mesangial hyperplasia with varying degrees and in different renal tubular damage were as follows: mild degree < moderate degree < severe degree (P<0.05). CONCLUSIONS: The pathological changes of mesangial proliferative glomerulonephritis are related to 24- hour urine protein, triglyceride, total cholesterol level, urine A1M, and Ccr level. The expression of TSP1 and PAI-1 in the mesenchyme of glomerular and renal tubules significantly increased with the severity of the disease, suggesting that TSP-1 and PAI-1 play an important role in the occurrence and development of mesangial proliferative glomerulonephritis.

Single-molecule real-time sequencing of the full-length transcriptome of loquat under low-temperature stress.

In this study, third-generation full-length (FL) transcriptome sequencing was performed of loquat using single-molecule real-time(SMRT) sequencing from the pooled cDNA of embryos of young loquat fruit under different low temperatures (three biological replicates for treatments of 1°C, -1°C, and -3°C, for 12 h or 24 h) and the control group(three biological replicates for treatments of room temperature), Illumina sequencing was used to correct FL transcriptome sequences. A total of 3 PacBio Iso-Seq libraries (1-2 kb, 2-3 kb and 3-6 kb) and 21 Illumina transcriptome libraries were constructed, a total of 13.41 Gb of clean reads were generated, which included 215,636 reads of insert (ROIs) and 121,654 FL, non-chimaric (FLNC) reads. Transcript clustering analysis of the FLNC reads revealed 76,586 consensus isoforms, and a total of 12,520 high-quality transcript sequences corrected with non-FL sequences were used for subsequent analysis. After the redundant reads were removed, 38,435 transcripts were obtained. A total of 27,905 coding DNA sequences (CDSs) were identified, and 407 long non-coding RNAs (lncRNAs) were ultimately predicted. Additionally, 24,832 simple sequence repeats (SSRs) were identified, and a total of 1,295 alternative splicing (AS) events were predicted. Furthermore, 37,993 transcripts were annotated in eight functional databases. This is the first study to perform SMRT sequencing of the FL transcriptome of loquat. The obtained transcriptomic data are conducive for further exploration of the mechanism of loquat freezing injury and thus serve as an important theoretical basis for generating new loquat material and for identifying new ways to improve loquat cold resistance.

Genetic Architecture of Abdominal Aortic Aneurysm in the Million Veteran Program.

BACKGROUND: Abdominal aortic aneurysm (AAA) is an important cause of cardiovascular mortality; however, its genetic determinants remain incompletely defined. In total, 10 previously identified risk loci explain a small fraction of AAA heritability. METHODS: We performed a genome-wide association study in the Million Veteran Program testing ≈18 million DNA sequence variants with AAA (7642 cases and 172 172 controls) in veterans of European ancestry with independent replication in up to 4972 cases and 99 858 controls. We then used mendelian randomization to examine the causal effects of blood pressure on AAA. We examined the association of AAA risk variants with aneurysms in the lower extremity, cerebral, and iliac arterial beds, and derived a genome-wide polygenic risk score (PRS) to identify a subset of the population at greater risk for disease. RESULTS: Through a genome-wide association study, we identified 14 novel loci, bringing the total number of known significant AAA loci to 24. In our mendelian randomization analysis, we demonstrate that a genetic increase of 10 mm Hg in diastolic blood pressure (odds ratio, 1.43 [95% CI, 1.24-1.66]; P=1.6×10-6), as opposed to systolic blood pressure (odds ratio, 1.06 [95% CI, 0.97-1.15]; P=0.2), likely has a causal relationship with AAA development. We observed that 19 of 24 AAA risk variants associate with aneurysms in at least 1 other vascular territory. A 29-variant PRS was strongly associated with AAA (odds ratioPRS, 1.26 [95% CI, 1.18-1.36]; PPRS=2.7×10-11 per SD increase in PRS), independent of family history and smoking risk factors (odds ratioPRS+family history+smoking, 1.24 [95% CI, 1.14-1.35]; PPRS=1.27×10-6). Using this PRS, we identified a subset of the population with AAA prevalence greater than that observed in screening trials informing current guidelines. CONCLUSIONS: We identify novel AAA genetic associations with therapeutic implications and identify a subset of the population at significantly increased genetic risk of AAA independent of family history. Our data suggest that extending current screening guidelines to include testing to identify those with high polygenic AAA risk, once the cost of genotyping becomes comparable with that of screening ultrasound, would significantly increase the yield of current screening at reasonable cost.

Genotyping Array Design and Data Quality Control in the Million Veteran Program.

The Million Veteran Program (MVP), initiated by the Department of Veterans Affairs (VA), aims to collect biosamples with consent from at least one million veterans. Presently, blood samples have been collected from over 800,000 enrolled participants. The size and diversity of the MVP cohort, as well as the availability of extensive VA electronic health records, make it a promising resource for precision medicine. MVP is conducting array-based genotyping to provide a genome-wide scan of the entire cohort, in parallel with whole-genome sequencing, methylation, and other 'omics assays. Here, we present the design and performance of the MVP 1.0 custom Axiom array, which was designed and developed as a single assay to be used across the multi-ethnic MVP cohort. A unified genetic quality-control analysis was developed and conducted on an initial tranche of 485,856 individuals, leading to a high-quality dataset of 459,777 unique individuals. 668,418 genetic markers passed quality control and showed high-quality genotypes not only on common variants but also on rare variants. We confirmed that, with non-European individuals making up nearly 30%, MVP's substantial ancestral diversity surpasses that of other large biobanks. We also demonstrated the quality of the MVP dataset by replicating established genetic associations with height in European Americans and African Americans ancestries. This current dataset has been made available to approved MVP researchers for genome-wide association studies and other downstream analyses. Further data releases will be available for analysis as recruitment at the VA continues and the cohort expands both in size and diversity.

Decoding the Genomics of Abdominal Aortic Aneurysm.

A key aspect of genomic medicine is to make individualized clinical decisions from personal genomes. We developed a machine-learning framework to integrate personal genomes and electronic health record (EHR) data and used this framework to study abdominal aortic aneurysm (AAA), a prevalent irreversible cardiovascular disease with unclear etiology. Performing whole-genome sequencing on AAA patients and controls, we demonstrated its predictive precision solely from personal genomes. By modeling personal genomes with EHRs, this framework quantitatively assessed the effectiveness of adjusting personal lifestyles given personal genome baselines, demonstrating its utility as a personal health management tool. We showed that this new framework agnostically identified genetic components involved in AAA, which were subsequently validated in human aortic tissues and in murine models. Our study presents a new framework for disease genome analysis, which can be used for both health management and understanding the biological architecture of complex diseases. VIDEO ABSTRACT.

Identification of potential core genes in triple negative breast cancer using bioinformatics analysis.

BACKGROUND: Triple-negative breast cancer (TNBC) is a subtype of breast cancer with poor clinical outcome and limited treatment options. Lacking molecular targets, chemotherapy is the main adjuvant treatment for TNBC patients. MATERIALS AND METHODS: To explore potential therapeutic targets for TNBC, we analyzed three microarray datasets (GSE38959, GSE45827, and GSE65194) derived from the Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) between TNBC and normal tissue. Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery to identify the pathways and functional annotation of DEGs. Protein-protein interaction of these DEGs was analyzed based on the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. In addition, we used the online Kaplan-Meier plotter survival analysis tool to evaluate the prognostic value of hub genes expression in breast cancer patients. RESULTS: A total of 278 upregulated DEGs and 173 downregulated DEGs were identified. Among them, ten hub genes with a high degree of connectivity were picked out. Overexpression of these hub genes was associated with unfavorable prognosis of breast cancer, especially, CCNB1 overexpression was observed and indicated poor outcome of TNBC. CONCLUSION: Our study suggests that CCNB1 was overexpressed in TNBC compared with normal breast tissue, and overexpression of CCNB1 was an unfavorable prognostic factor of TNBC patients. Further study is needed to explore the value of CCNB1 in the treatment of TNBC.

Cloud-based interactive analytics for terabytes of genomic variants data.

MOTIVATION: Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. RESULTS: We present interactive analytics using a cloud-based columnar database built on Dremel to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate such Big Data computing paradigms can provide orders of magnitude faster turnaround for common genomic analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds. Using this method, we assessed a study population of 475 deeply sequenced human genomes for genomic call rate, genotype and allele frequency distribution, variant density across the genome, and pharmacogenomic information. AVAILABILITY AND IMPLEMENTATION: Our analysis framework is implemented in Google Cloud Platform and BigQuery. Codes are available at https://github.com/StanfordBioinformatics/mvp_aaa_codelabs. CONTACT: cuiping@stanford.edu or ptsao@stanford.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data.

High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework.