Publications by authors named "Nicholas J Schork"

320 Publications

Cross-Species and Human Inter-Tissue Network Analysis of Genes Implicated in Longevity and Aging Reveal Strong Support for Nutrient Sensing.

Front Genet 2021 27;12:719713. Epub 2021 Aug 27.

Department of Quantitative Medicine, The Translational Genomics Research Institute (TGen), Phoenix, AZ, United States.

Intensive research efforts have been undertaken to slow human aging and therefore potentially delay the onset of age-related diseases. These efforts have generated an enormous amount of high-throughput data covering different levels in the physiologic hierarchy, e.g., genetic, epigenetic, transcriptomic, proteomic, and metabolomic, etc. We gathered 15 independent sources of information about genes potentially involved in human longevity and lifespan ( = 5836) and subjected them to various integrated analyses. Many of these genes were initially identified in non-human species, and we investigated their orthologs in three non-human species [i.e., mice ( = 967), fruit fly ( = 449), and worm ( = 411)] for further analysis. We characterized experimentally determined protein-protein interaction networks (PPIN) involving each species' genes from 9 known protein databases and studied the enriched biological pathways among the individually constructed PPINs. We observed three important signaling pathways: FoxO signaling, mTOR signaling, and autophagy to be common and highly enriched in all four species (-value ≤ 0.001). Our study implies that the interaction of proteins involved in the mechanistic target of rapamycin (mTOR) signaling pathway is somewhat limited to each species or that a "rewiring" of specific networks has taken place over time. To corroborate our findings, we repeated our analysis in 43 different human tissues. We investigated conserved modules in various tissue-specific PPINs of the longevity-associated genes based upon their protein expression. This analysis also revealed mTOR signaling as shared biological processes across four different human tissue-specific PPINs for liver, heart, skeletal muscle, and adipose tissue. Further, we explored our results' translational potential by assessing the protein interactions with all the reported drugs and compounds that have been experimentally verified to promote longevity in the three-comparator species. We observed that the target proteins of the FDA-approved drug rapamycin (a known inhibitor of mTOR) were conserved across all four species. Drugs like melatonin and metformin exhibited shared targets with rapamycin in the human PPIN. The detailed information about the curated gene list, cross-species orthologs, PPIN, and pathways was assembled in an interactive data visualization portal using RStudio's Shiny framework (https://agingnetwork.shinyapps.io/frontiers/).
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http://dx.doi.org/10.3389/fgene.2021.719713DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8430347PMC
August 2021

Correction: Association Between Improvement in Baseline Mood and Long-Term Use of a Mindfulness and Meditation App: Observational Study.

JMIR Ment Health 2021 Jun 30;8(6):e28132. Epub 2021 Jun 30.

Department of Biomedial Informatics, University of California San Diego, San Diego, CA, United States.

[This corrects the article DOI: 10.2196/12617.].
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http://dx.doi.org/10.2196/28132DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280831PMC
June 2021

Genetic signature of human longevity in PKC and NF-κB signaling.

Aging Cell 2021 07 1;20(7):e13362. Epub 2021 Jul 1.

Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA.

Gene variants associated with longevity are also associated with protection against cognitive decline, dementia and Alzheimer's disease, suggesting that common physiologic pathways act at the interface of longevity and cognitive function. To test the hypothesis that variants in genes implicated in cognitive function may promote exceptional longevity, we performed a comprehensive 3-stage study to identify functional longevity-associated variants in ~700 candidate genes in up to 450 centenarians and 500 controls by target capture sequencing analysis. We found an enrichment of longevity-associated genes in the nPKC and NF-κB signaling pathways by gene-based association analyses. Functional analysis of the top three gene variants (NFKBIA, CLU, PRKCH) suggests that non-coding variants modulate the expression of cognate genes, thereby reducing signaling through the nPKC and NF-κB. This matches genetic studies in multiple model organisms, suggesting that the evolutionary conservation of reduced PKC and NF-κB signaling pathways in exceptional longevity may include humans.
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http://dx.doi.org/10.1111/acel.13362DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282271PMC
July 2021

Improved methods for RNAseq-based alternative splicing analysis.

Sci Rep 2021 05 24;11(1):10740. Epub 2021 May 24.

Quantitative Medicine and Systems Biology Division, Translational Genomics Research Institute, Phoenix, AZ, USA.

The robust detection of disease-associated splice events from RNAseq data is challenging due to the potential confounding effect of gene expression levels and the often limited number of patients with relevant RNAseq data. Here we present a novel statistical approach to splicing outlier detection and differential splicing analysis. Our approach tests for differences in the percentages of sequence reads representing local splice events. We describe a software package called Bisbee which can predict the protein-level effect of splice alterations, a key feature lacking in many other splicing analysis resources. We leverage Bisbee's prediction of protein level effects as a benchmark of its capabilities using matched sets of RNAseq and mass spectrometry data from normal tissues. Bisbee exhibits improved sensitivity and specificity over existing approaches and can be used to identify tissue-specific splice variants whose protein-level expression can be confirmed by mass spectrometry. We also applied Bisbee to assess evidence for a pathogenic splicing variant contributing to a rare disease and to identify tumor-specific splice isoforms associated with an oncogenic mutation. Bisbee was able to rediscover previously validated results in both of these cases and also identify common tumor-associated splice isoforms replicated in two independent melanoma datasets.
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http://dx.doi.org/10.1038/s41598-021-89938-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144374PMC
May 2021

Soluble α-synuclein-antibody complexes activate the NLRP3 inflammasome in hiPSC-derived microglia.

Proc Natl Acad Sci U S A 2021 Apr;118(15)

Neurodegeneration New Medicines Center, The Scripps Research Institute, La Jolla, CA 92037;

Parkinson's disease is characterized by accumulation of α-synuclein (αSyn). Release of oligomeric/fibrillar αSyn from damaged neurons may potentiate neuronal death in part via microglial activation. Heretofore, it remained unknown if oligomeric/fibrillar αSyn could activate the nucleotide-binding oligomerization domain (NOD)-like receptor (NLR) family pyrin domain-containing 3 (NLRP3) inflammasome in human microglia and whether anti-αSyn antibodies could prevent this effect. Here, we show that αSyn activates the NLRP3 inflammasome in human induced pluripotent stem cell (hiPSC)-derived microglia (hiMG) via dual stimulation involving Toll-like receptor 2 (TLR2) engagement and mitochondrial damage. In vitro, hiMG can be activated by mutant (A53T) αSyn secreted from hiPSC-derived A9-dopaminergic neurons. Surprisingly, αSyn-antibody complexes enhanced rather than suppressed inflammasome-mediated interleukin-1β (IL-1β) secretion, indicating these complexes are neuroinflammatory in a human context. A further increase in inflammation was observed with addition of oligomerized amyloid-β peptide (Aβ) and its cognate antibody. In vivo, engraftment of hiMG with αSyn in humanized mouse brain resulted in caspase-1 activation and neurotoxicity, which was exacerbated by αSyn antibody. These findings may have important implications for antibody therapies aimed at depleting misfolded/aggregated proteins from the human brain, as they may paradoxically trigger inflammation in human microglia.
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http://dx.doi.org/10.1073/pnas.2025847118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054017PMC
April 2021

Characterizing Emotional State Transitions During Prolonged Use of a Mindfulness and Meditation App: Observational Study.

JMIR Ment Health 2021 Mar 2;8(3):e19832. Epub 2021 Mar 2.

Bioinformatics and Systems Biology, University California San Diego, San Diego, CA, United States.

Background: The increasing demand for mental health care, a lack of mental health care providers, and unequal access to mental health care services have created a need for innovative approaches to mental health care. Digital device apps, including digital therapeutics, that provide recommendations and feedback for dealing with stress, depression, and other mental health issues can be used to adjust mood and ultimately show promise to help meet this demand. In addition, the recommendations delivered through such apps can also be tailored to an individual's needs (ie, personalized) and thereby potentially provide greater benefits than traditional "one-size-fits-all" recommendations.

Objective: This study aims to characterize individual transitions from one emotional state to another during the prolonged use of a digital app designed to provide a user with guided meditations based on their initial, potentially negative, emotional state. Understanding the factors that mediate such transitions can lead to improved recommendations for specific mindfulness and meditation interventions or activities (MMAs) provided in mental health apps.

Methods: We analyzed data collected during the use of the Stop, Breathe & Think (SBT) mindfulness app. The SBT app prompts users to input their emotional state before and immediately after engaging with MMAs recommended by the app. Data were collected from more than 650,000 SBT users engaging in nearly 5 million MMAs. We limited the scope of our analysis to users with 10 or more MMA sessions that included at least 6 basal emotional state evaluations. Using clustering techniques, we grouped emotions recorded by individual users and then applied longitudinal mixed effect models to assess the associations between individual recommended MMAs and transitions from one group of emotions to another.

Results: We found that basal emotional states have a strong influence on transitions from one emotional state to another after MMA engagement. We also found that different MMAs impact these transitions, and many were effective in eliciting a healthy transition but only under certain conditions. In addition, we observed gender and age effects on these transitions.

Conclusions: We found that the initial emotional state of an SBT app user determines the type of SBT MMAs that will have a favorable effect on their transition from one emotional state to another. Our results have implications for the design and use of guided mental health recommendations for digital device apps.
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http://dx.doi.org/10.2196/19832DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7967231PMC
March 2021

Conserved Genomic Terminals of SARS-CoV-2 as Coevolving Functional Elements and Potential Therapeutic Targets.

mSphere 2020 11 25;5(6). Epub 2020 Nov 25.

The Translational Genomics Research Institute (TGen), Phoenix, Arizona, USA

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 40 million people worldwide, with over 1 million deaths as of October 2020 and with multiple efforts in the development and testing of antiviral drugs and vaccines under way. In order to gain insights into SARS-CoV-2 evolution and drug targets, we investigated how and to what extent the SARS-CoV-2 genome sequence differs from those of other well-characterized human and animal coronavirus genomes, as well as how polymorphic SARS-CoV-2 genomes are generally. We ultimately sought to identify features in the SARS-CoV-2 genome that may contribute to its viral replication, host pathogenicity, and vulnerabilities. Our analyses suggest the presence of unique sequence signatures in the 3' untranslated region (3'-UTR) of betacoronavirus lineage B, which phylogenetically encompasses SARS-CoV-2 and SARS-CoV as well as multiple groups of bat and animal coronaviruses. In addition, we identified genome-wide patterns of variation across different SARS-CoV-2 strains that likely reflect the effects of selection. Finally, we provide evidence for a possible host-microRNA-mediated interaction between the 3'-UTR and human microRNA hsa-miR-1307-3p based on the results of multiple computational target prediction analyses and an assessment of similar interactions involving the influenza A H1N1 virus. This interaction also suggests a possible survival mechanism, whereby a mutation in the SARS-CoV-2 3'-UTR leads to a weakened host immune response. The potential roles of host microRNAs in SARS-CoV-2 replication and infection and the exploitation of conserved features in the 3'-UTR as therapeutic targets warrant further investigation. The coronavirus disease 2019 (COVID-19) outbreak is having a dramatic global effect on public health and the economy. As of October 2020, SARS-CoV-2 has been detected in over 189 countries, has infected over 40 million people, and is responsible for more than 1 million deaths. The genome of SARS-CoV-2 is small but complex, and its functions and interactions with human host factors are being studied extensively. The significance of our study is that, using extensive SARS-CoV-2 genome analysis techniques, we identified potential interacting human host microRNA targets that share similarity with those of influenza A virus H1N1. Our study results will allow the development of virus-host interaction models that will enhance our understanding of SARS-CoV-2 pathogenesis and motivate the exploitation of both the interacting viral and host factors as therapeutic targets.
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http://dx.doi.org/10.1128/mSphere.00754-20DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7690956PMC
November 2020

signatureSearch: environment for gene expression signature searching and functional interpretation.

Nucleic Acids Res 2020 12;48(21):e124

Institute for Integrative Genome Biology, 1207F Genomics Building, University of California, Riverside, CA 92521, USA.

signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases.
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http://dx.doi.org/10.1093/nar/gkaa878DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708038PMC
December 2020

Impacts of personal DNA ancestry testing.

J Community Genet 2021 Jan 13;12(1):37-52. Epub 2020 Aug 13.

Departments of Family Medicine and Public Health, Psychiatry, and Medicine, University of California San Diego, La Jolla, CA, USA.

Consumer uptake of direct-to-consumer (DTC) DNA ancestry testing is accelerating, yet few empirical studies have examined test impacts on recipients despite the DTC ancestry industry being two decades old. Participants in a longitudinal cohort study of response to health-related DTC genomic testing also received personal DNA ancestry testing at no additional cost. Baseline survey data from the primary study were analyzed together with responses to an additional follow-up survey focused on the response to ancestry results. Ancestry results were generated for 3466 individuals. Of those, 1317 accessed their results, and 322 individuals completed an ancestry response survey, in other words, approximately one in ten who received ancestry testing responded to the survey. Self-reported race/ethnicity was predictive of those most likely to view their results. While 46% of survey responders (N = 147) reported their ancestry results as surprising or unexpected, less than 1% (N = 3) were distressed by them. Importantly, however, 21% (N = 67) reported that their results reshaped their personal identity. Most (81%; N = 260) planned to share results with family, and 12% (N = 39) intended to share results with a healthcare provider. Many (61%; N = 196) reported test benefits (e.g., health insights), while 12% (N = 38) reported negative aspects (e.g., lack of utility). Over half (N = 162) reported being more likely to have other genetic tests in the future. DNA ancestry testing affected individuals with respect to personal identity, intentions to share genetic information with family and healthcare providers, and the likelihood to engage with other genetic tests in the future. These findings have implications for medical care and research, specifically, provider readiness to engage with genetic ancestry information.
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http://dx.doi.org/10.1007/s12687-020-00481-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846620PMC
January 2021

A 25-y longitudinal dolphin cohort supports that long-lived individuals in same environment exhibit variation in aging rates.

Proc Natl Acad Sci U S A 2020 08 10;117(34):20950-20958. Epub 2020 Aug 10.

Seraphina Therapeutics, Inc., San Diego, CA 92106.

While it is believed that humans age at different rates, a lack of robust longitudinal human studies using consensus biomarkers meant to capture aging rates has hindered an understanding of the degree to which individuals vary in their rates of aging. Because bottlenose dolphins are long-lived mammals that develop comorbidities of aging similar to humans, we analyzed data from a well-controlled, 25-y longitudinal cohort of 144 US Navy dolphins housed in the same oceanic environment. Our analysis focused on 44 clinically relevant hematologic and clinical chemistry measures recorded during routine blood draws throughout the dolphins' lifetimes. Using stepwise regression and general linear models that accommodate correlations between measures obtained on individual dolphins, we demonstrate that, in a manner similar to humans, dolphins exhibit independent and linear age-related declines in four of these measures: hemoglobin, alkaline phosphatase, platelets, and lymphocytes. Using linear regressions and analyses of covariance with post hoc Tukey-Kramer tests to compare slopes (i.e., linear age-related rates) of our four aging rate biomarkers among 34 individual dolphins aging from 10 y to up to 40 y old, we could identify slow and accelerated agers and differentiate subgroups that were more or less likely to develop anemia and lymphopenia. This study successfully documents aging rate differences over the lifetime of long-lived individuals in a controlled environment. Our study suggests that nonenvironmental factors influencing aging rate biomarkers, including declining hemoglobin and anemia, may be targeted to delay the effects of aging in a compelling model of human biology.
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http://dx.doi.org/10.1073/pnas.1918755117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456138PMC
August 2020

Conserved Genomic Terminals of SARS-CoV-2 as Co-evolving Functional Elements and Potential Therapeutic Targets.

bioRxiv 2020 Jul 6. Epub 2020 Jul 6.

The Translational Genomics Research Institute (TGen), Phoenix, AZ.

To identify features in the genome of the SARS-CoV-2 pathogen responsible for the COVID-19 pandemic that may contribute to its viral replication, host pathogenicity, and vulnerabilities, we investigated how and to what extent the SARS-CoV-2 genome sequence differs from other well-characterized human and animal coronavirus genomes. Our analyses suggest the presence of unique sequence signatures in the 3'-untranslated region (UTR) of betacoronavirus lineage B, which phylogenetically encompasses SARS-CoV-2, SARS-CoV, as well as multiple groups of bat and animal coronaviruses. In addition, we identified genome-wide patterns of variation across different SARS-CoV-2 strains that likely reflect the effects of selection. Finally, we provide evidence for a possible host microRNA-mediated interaction between the 3'-UTR and human microRNA hsa-miR-1307-3p based on predicted, yet extensive, complementary base-pairings and similar interactions involving the Influenza A H1N1 virus. This interaction also suggests a possible survival mechanism, whereby a mutation in the SARS-CoV-2 3'-UTR leads to a weakened host immune response. The potential roles of host microRNAs in SARS-CoV-2 replication and infection, and the exploitation of conserved features in the 3'-UTR as therapeutic targets warrant further investigation.
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http://dx.doi.org/10.1101/2020.07.06.190207DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359523PMC
July 2020

Strategies for Testing Intervention Matching Schemes in Cancer.

Clin Pharmacol Ther 2020 09 24;108(3):542-552. Epub 2020 Jul 24.

The Translational Genomics Research Institute (TGen), Phoenix, Arizona, USA.

Personalized medicine, or the tailoring of health interventions to an individual's nuanced and often unique genetic, biochemical, physiological, behavioral, and/or exposure profile, is seen by many as a biological necessity given the great heterogeneity of pathogenic processes underlying most diseases. However, testing and ultimately proving the benefit of strategies or algorithms connecting the mechanisms of action of specific interventions to patient pathophysiological profiles (referred to here as "intervention matching schemes" (IMS)) is complex for many reasons. We argue that IMS are likely to be pervasive, if not ubiquitous, in future health care, but raise important questions about their broad deployment and the contexts within which their utility can be proven. For example, one could question the need to, the efficiency associated with, and the reliability of, strategies for comparing competing or perhaps complementary IMS. We briefly summarize some of the more salient issues surrounding the vetting of IMS in cancer contexts and argue that IMS are at the foundation of many modern clinical trials and intervention strategies, such as basket, umbrella, and adaptive trials. In addition, IMS are at the heart of proposed "rapid learning systems" in hospitals, and implicit in cell replacement strategies, such as cytotoxic T-cell therapies targeting patient-specific neo-antigen profiles. We also consider the need for sensitivity to issues surrounding the deployment of IMS and comment on directions for future research.
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http://dx.doi.org/10.1002/cpt.1947DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901602PMC
September 2020

Transcriptomic evidence that von Economo neurons are regionally specialized extratelencephalic-projecting excitatory neurons.

Nat Commun 2020 03 3;11(1):1172. Epub 2020 Mar 3.

Allen Institute for Brain Science, Seattle, WA, USA.

von Economo neurons (VENs) are bipolar, spindle-shaped neurons restricted to layer 5 of human frontoinsula and anterior cingulate cortex that appear to be selectively vulnerable to neuropsychiatric and neurodegenerative diseases, although little is known about other VEN cellular phenotypes. Single nucleus RNA-sequencing of frontoinsula layer 5 identifies a transcriptomically-defined cell cluster that contained VENs, but also fork cells and a subset of pyramidal neurons. Cross-species alignment of this cell cluster with a well-annotated mouse classification shows strong homology to extratelencephalic (ET) excitatory neurons that project to subcerebral targets. This cluster also shows strong homology to a putative ET cluster in human temporal cortex, but with a strikingly specific regional signature. Together these results suggest that VENs are a regionally distinctive type of ET neuron. Additionally, we describe the first patch clamp recordings of VENs from neurosurgically-resected tissue that show distinctive intrinsic membrane properties relative to neighboring pyramidal neurons.
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http://dx.doi.org/10.1038/s41467-020-14952-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054400PMC
March 2020

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Addict Biol 2021 01 16;26(1):e12880. Epub 2020 Feb 16.

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, RWTH Aachen University, Aachen, Germany.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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http://dx.doi.org/10.1111/adb.12880DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429266PMC
January 2021

Genetic Support for Longevity-Enhancing Drug Targets: Issues, Preliminary Data, and Future Directions.

J Gerontol A Biol Sci Med Sci 2019 11;74(Suppl_1):S61-S71

Department of Quantitative Medicine and Systems Biology, The Translational Genomics Research Institute (TGen), Phoenix, Arizona.

Interventions meant to promote longevity and healthy aging have often been designed or observed to modulate very specific gene or protein targets. If there are naturally occurring genetic variants in such a target that affect longevity as well as the molecular function of that target (eg, the variants influence the expression of the target, acting as "expression quantitative trait loci" or "eQTLs"), this could support a causal relationship between the pharmacologic modulation of the target and longevity and thereby validate the target at some level. We considered the gene targets of many pharmacologic interventions hypothesized to enhance human longevity and explored how many variants there are in those targets that affect gene function (eg, as expression quantitative trait loci). We also determined whether variants in genes associated with longevity-related phenotypes affect gene function or are in linkage disequilibrium with variants that do, and whether pharmacologic studies point to compounds exhibiting activity against those genes. Our results are somewhat ambiguous, suggesting that integrating genetic association study results with functional genomic and pharmacologic studies is necessary to shed light on genetically mediated targets for longevity-enhancing drugs. Such integration will require more sophisticated data sets, phenotypic definitions, and bioinformatics approaches to be useful.
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http://dx.doi.org/10.1093/gerona/glz206DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330475PMC
November 2019

Multi-Omic Biological Age Estimation and Its Correlation With Wellness and Disease Phenotypes: A Longitudinal Study of 3,558 Individuals.

J Gerontol A Biol Sci Med Sci 2019 11;74(Suppl_1):S52-S60

Institute for Systems Biology, Seattle, Washington.

Biological age (BA), derived from molecular and physiological measurements, has been proposed to better predict mortality and disease than chronological age (CA). In the present study, a computed estimate of BA was investigated longitudinally in 3,558 individuals using deep phenotyping, which encompassed a broad range of biological processes. The Klemera-Doubal algorithm was applied to longitudinal data consisting of genetic, clinical laboratory, metabolomic, and proteomic assays from individuals undergoing a wellness program. BA was elevated relative to CA in the presence of chronic diseases. We observed a significantly lower rate of change than the expected ~1 year/year (to which the estimation algorithm was constrained) in BA for individuals participating in a wellness program. This observation suggests that BA is modifiable and suggests that a lower BA relative to CA may be a sign of healthy aging. Measures of metabolic health, inflammation, and toxin bioaccumulation were strong predictors of BA. BA estimation from deep phenotyping was seen to change in the direction expected for both positive and negative health conditions. We believe BA represents a general and interpretable "metric for wellness" that may aid in monitoring aging over time.
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http://dx.doi.org/10.1093/gerona/glz220DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6853785PMC
November 2019

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa.

Nat Genet 2019 08 15;51(8):1207-1214. Epub 2019 Jul 15.

Clinical Genetics Unit, Department of Woman and Child Health, University of Padova, Padova, Italy.

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness, affecting 0.9-4% of women and 0.3% of men, with twin-based heritability estimates of 50-60%. Mortality rates are higher than those in other psychiatric disorders, and outcomes are unacceptably poor. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI) and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.
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http://dx.doi.org/10.1038/s41588-019-0439-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779477PMC
August 2019

Power and Design Issues in Crossover-Based N-Of-1 Clinical Trials with Fixed Data Collection Periods.

Healthcare (Basel) 2019 Jul 2;7(3). Epub 2019 Jul 2.

Quantitative Medicine and Systems Biology, The Translational Genomics Research Institute (TGen), an affiliate of the City of Hope National Medical Center, 445 North Fifth Street, Phoenix, AZ 85004, USA.

"N-of-1," or single subject, clinical trials seek to determine if an intervention strategy is more efficacious for an individual than an alternative based on an objective, empirical, and controlled study. The design of such trials is typically rooted in a simple crossover strategy with multiple intervention response evaluation periods. The effect of serial correlation between measurements, the number of evaluation periods, the use of washout periods, heteroscedasticity (i.e., unequal variances among responses to the interventions) and intervention-associated carry-over phenomena on the power of such studies is crucially important for putting the yield and feasibility of N-of-1 trial designs into context. We evaluated the effect of these phenomena on the power of different designs for N-of-1 trials using analytical theory based on standard likelihood principles assuming an autoregressive lag 1, i.e., AR(1), serial correlation structure among the measurements as well as simulation studies. By evaluating the power to detect effects in many different settings, we show that the influence of serial correlation and heteroscedasticity on power can be substantial, but can also be mitigated to some degree through the use of appropriate multiple evaluation periods. We also show that the detection of certain types of carry-over effects can be heavily influenced by design considerations as well.
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http://dx.doi.org/10.3390/healthcare7030084DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6787650PMC
July 2019

Artificial Intelligence and Personalized Medicine.

Cancer Treat Res 2019 ;178:265-283

Department of Quantitative Medicine, The Translational Genomics Research Institute (TGen), Phoenix, AZ, USA.

The development of high-throughput, data-intensive biomedical research assays and technologies has created a need for researchers to develop strategies for analyzing, integrating, and interpreting the massive amounts of data they generate. Although a wide variety of statistical methods have been designed to accommodate 'big data,'  experiences with the use of artificial intelligence (AI) techniques suggest that they might be particularly appropriate. In addition,  the results of the application of these assays reveal a great heterogeneity in the pathophysiologic factors and processes that contribute to disease, suggesting that there is a need to tailor, or 'personalize,' medicines to the nuanced and often unique features possessed by individual patients. Given how important data-intensive assays are to revealing appropriate intervention targets and strategies for  treating an individual with a disease, AI can play an important role in the development of personalized medicines. We describe many areas where AI can play such a role and argue that AI's ability to advance personalized medicine will depend critically on not only the refinement of relevant assays, but also on ways of storing, aggregating, accessing, and ultimately integrating, the data they produce. We also point out the limitations of many AI techniques in developing personalized medicines as well as consider areas for further research.
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http://dx.doi.org/10.1007/978-3-030-16391-4_11DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7580505PMC
June 2019

Rare variant phasing using paired tumor:normal sequence data.

BMC Bioinformatics 2019 May 27;20(1):265. Epub 2019 May 27.

Human Biology Program, J. Craig Venter Institute, La Jolla, CA, USA.

Background: In standard high throughput sequencing analysis, genetic variants are not assigned to a homologous chromosome of origin. This process, called haplotype phasing, can reveal information important for understanding the relationship between genetic variants and biological phenotypes. For example, in genes that carry multiple heterozygous missense variants, phasing resolves whether one or both gene copies are altered. Here, we present a novel approach to phasing variants that takes advantage of unique properties of paired tumor:normal sequencing data from cancer studies.

Results: VAF phasing uses changes in variant allele frequency (VAF) between tumor and normal samples in regions of somatic chromosomal gain or loss to phase germline variants. We apply VAF phasing to 6180 samples from the Cancer Genome Atlas (TCGA) and demonstrate that our method is highly concordant with other standard phasing methods, and can phase an average of 33% more variants than other read-backed phasing methods. Using variant annotation tools designed to score gene haplotypes, we find a suggestive association between carrying multiple missense variants in a single copy of a cancer predisposition gene and earlier age of cancer diagnosis.

Conclusions: VAF phasing exploits unique properties of tumor genomes to increase the number of germline variants that can be phased over standard read-backed methods in paired tumor:normal samples. Our phase-informed association testing results call attention to the need to develop more tools for assessing the joint effect of multiple genetic variants.
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http://dx.doi.org/10.1186/s12859-019-2753-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6537421PMC
May 2019

Association Between Improvement in Baseline Mood and Long-Term Use of a Mindfulness and Meditation App: Observational Study.

JMIR Ment Health 2019 05 8;6(5):e12617. Epub 2019 May 8.

Department of Biomedial Informatics, University of California San Diego, San Diego, CA, United States.

Background: The use of smartphone apps to monitor and deliver health care guidance and interventions has received considerable attention recently, particularly with regard to behavioral disorders, stress relief, negative emotional state, and poor mood in general. Unfortunately, there is little research investigating the long-term and repeated effects of apps meant to impact mood and emotional state.

Objective: We aimed to investigate the effects of both immediate point-of-intervention and long-term use (ie, at least 10 engagements) of a guided meditation and mindfulness smartphone app on users' emotional states. Data were collected from users of a mobile phone app developed by the company Stop, Breathe & Think (SBT) for achieving emotional wellness. To explore the long-term effects, we assessed changes in the users' basal emotional state before they completed an activity (eg, a guided meditation). We also assessed the immediate effects of the app on users' emotional states from preactivity to postactivity.

Methods: The SBT app collects information on the emotional state of the user before and after engagement in one or several mediation and mindfulness activities. These activities are recommended and provided by the app based on user input. We considered data on over 120,000 users of the app who collectively engaged in over 5.5 million sessions with the app during an approximate 2-year period. We focused our analysis on users who had at least 10 engagements with the app over an average of 6 months. We explored the changes in the emotional well-being of individuals with different emotional states at the time of their initial engagement with the app using mixed-effects models. In the process, we compared 2 different methods of classifying emotional states: (1) an expert-defined a priori mood classification and (2) an empirically driven cluster-based classification.

Results: We found that among long-term users of the app, there was an association between the length of use and a positive change in basal emotional state (4% positive mood increase on a 2-point scale every 10 sessions). We also found that individuals who were anxious or depressed tended to have a favorable long-term emotional transition (eg, from a sad emotional state to a happier emotional state) after using the app for an extended period (the odds ratio for achieving a positive emotional state was 3.2 and 6.2 for anxious and depressed individuals, respectively, compared with users with fewer sessions).

Conclusions: Our analyses provide evidence for an association between both immediate and long-term use of an app providing guided meditations and improvements in the emotional state.
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http://dx.doi.org/10.2196/12617DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6707590PMC
May 2019

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Nat Genet 2019 05 1;51(5):793-803. Epub 2019 May 1.

Department of Psychiatry, Weill Cornell Medical College, New York, NY, USA.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
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http://dx.doi.org/10.1038/s41588-019-0397-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956732PMC
May 2019

Combinatorial interactions of genetic variants in human cardiomyopathy.

Nat Biomed Eng 2019 02 7;3(2):147-157. Epub 2019 Feb 7.

Division of Cardiology, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.

Dilated cardiomyopathy (DCM) is a leading cause of morbidity and mortality worldwide; yet how genetic variation and environmental factors impact DCM heritability remains unclear. Here, we report that compound genetic interactions between DNA sequence variants contribute to the complex heritability of DCM. By using genetic data from a large family with a history of DCM, we discovered that heterozygous sequence variants in the () and () genes cose-gregate in individuals affected by DCM. In vitro studies of patient-derived and isogenic human-pluripotent-stem-cell-derived cardio-myocytes that were genome-edited via CRISPR to create an allelic series of and variants revealed that cardiomyocytes with both and variants display reduced contractility and sarcomeres that are less organized. Analyses of mice genetically engineered to harbour these human and variants show that stress on the heart may also influence the variable penetrance and expressivity of DCM-associated genetic variants in vivo. We conclude that compound genetic variants can interact combinatorially to induce DCM, particularly when influenced by other disease-provoking stressors.
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http://dx.doi.org/10.1038/s41551-019-0348-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6433174PMC
February 2019

Fine mapping and subphenotyping implicates ADRA1B gene variants in psoriasis susceptibility in a Chinese population.

Epigenomics 2019 02 20;11(4):455-467. Epub 2019 Feb 20.

HumanBiology, J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, USA.

Aim: A genomic region on 5q33.3 lies between and encompasses the IL12B and PTTG1 genes, and contains many potential psoriasis causal variants. We aimed to further examine the influence of variants in and around this region.

Materials & Methods: We used least absolute shrinkage and selection operator (LASSO)-based regression analysis to assess independent contributions of 2171 variants to psoriasis susceptibility and tested them for association with different clinical psoriasis subtypes.

Results: We found that ADRA1B gene variants contribute to psoriasis in Chinese population. ADRA1B gene variants have a stronger association with moderate-to-severe disease group and an earlier age at onset of psoriasis than IL-12B and PTTG1 variants.

Conclusion: The association of variants in the ADRA1B gene with psoriasis could explain why variants in the IL-12B, ADRA1B and PTTG1 gene regions are associated with psoriasis.
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http://dx.doi.org/10.2217/epi-2018-0131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7132640PMC
February 2019

An investigation of indirect effects of personality features on anorexia nervosa severity through interoceptive dysfunction in individuals with lifetime anorexia nervosa diagnoses.

Int J Eat Disord 2019 02 12;52(2):200-205. Epub 2019 Jan 12.

Department of Psychology, Florida State University, Tallahassee, Florida.

Objective: This study examined a hypothesized pathway by which interoceptive dysfunction accounted for associations between personality features (harm avoidance, self-directedness, and perfectionism) and anorexia nervosa (AN) severity (indicated by drive for thinness, eating disorder-related preoccupations and rituals, and body mass index).

Method: The study sample (n = 270, mean age = 28.47, 95.2% female, 98% White/Caucasian) consisted of probands and biological relatives who met DSM-IV criteria for lifetime diagnoses of AN (omitting criterion D, amenorrhea) drawn from the Price Foundation Anorexia Nervosa Affected Relative Pairs Study (AN-ARP). Participants completed measures assessing personality, interoceptive dysfunction, and eating pathology.

Results: Associations between personality features of low self-directedness and high perfectionism and indicators of AN severity (drive for thinness and eating disorder-related preoccupations and rituals) were significant, as were the hypothesized indirect pathways through interoceptive dysfunction. Neither harm avoidance nor body mass index was significantly related to other study variables, and the proposed indirect pathways involving these variables were not significant.

Discussion: Findings suggest that certain personality features may relate to AN severity, in part, through their associations with interoceptive dysfunction. Future research should examine prospective associations and the value of interventions targeting interoceptive dysfunction for interrupting the link between personality and AN severity.
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http://dx.doi.org/10.1002/eat.23008DOI Listing
February 2019

Single-nucleus and single-cell transcriptomes compared in matched cortical cell types.

PLoS One 2018 26;13(12):e0209648. Epub 2018 Dec 26.

Allen Institute for Brain Science, Seattle, WA, United States of America.

Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0209648PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6306246PMC
May 2019

Efficient region-based test strategy uncovers genetic risk factors for functional outcome in bipolar disorder.

Eur Neuropsychopharmacol 2019 01 29;29(1):156-170. Epub 2018 Nov 29.

U.S. Department of Health & Human Services, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20894, United States.

Genome-wide association studies of case-control status have advanced the understanding of the genetic basis of psychiatric disorders. Further progress may be gained by increasing sample size but also by new analysis strategies that advance the exploitation of existing data, especially for clinically important quantitative phenotypes. The functionally-informed efficient region-based test strategy (FIERS) introduced herein uses prior knowledge on biological function and dependence of genotypes within a powerful statistical framework with improved sensitivity and specificity for detecting consistent genetic effects across studies. As proof of concept, FIERS was used for the first genome-wide single nucleotide polymorphism (SNP)-based investigation on bipolar disorder (BD) that focuses on an important aspect of disease course, the functional outcome. FIERS identified a significantly associated locus on chromosome 15 (hg38: chr15:48965004 - 49464789 bp) with consistent effect strength between two independent studies (GAIN/TGen: European Americans, BOMA: Germans; n = 1592 BD patients in total). Protective and risk haplotypes were found on the most strongly associated SNPs. They contain a CTCF binding site (rs586758); CTCF sites are known to regulate sets of genes within a chromatin domain. The rs586758 - rs2086256 - rs1904317 haplotype is located in the promoter flanking region of the COPS2 gene, close to microRNA4716, and the EID1, SHC4, DTWD1 genes as plausible biological candidates. While implication with BD is novel, COPS2, EID1, and SHC4 are known to be relevant for neuronal differentiation and function and DTWD1 for psychopharmacological side effects. The test strategy FIERS that enabled this discovery is equally applicable for tag SNPs and sequence data.
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http://dx.doi.org/10.1016/j.euroneuro.2018.10.005DOI Listing
January 2019

Report: NIA workshop on translating genetic variants associated with longevity into drug targets.

Geroscience 2018 12 29;40(5-6):523-538. Epub 2018 Oct 29.

National Institute on Aging, Bethesda, MD, USA.

To date, candidate gene and genome-wide association studies (GWAS) have led to the discovery of longevity-associated variants (LAVs) in genes such as FOXO3A and APOE. Unfortunately, translating variants into drug targets is challenging for any trait, and longevity is no exception. Interdisciplinary and integrative multi-omics approaches are needed to understand how LAVs affect longevity-related phenotypes at the molecular physiologic level in order to leverage their discovery to identify new drug targets. The NIA convened a workshop in August 2017 on emerging and novel in silico (i.e., bioinformatics and computational) approaches to the translation of LAVs into drug targets. The goal of the workshop was to identify ways of enabling, enhancing, and facilitating interactions among researchers from different disciplines whose research considers either the identification of LAVs or the mechanistic or causal pathway(s) and protective factors they influence for discovering drug targets. Discussions among the workshop participants resulted in the identification of critical needs for enabling the translation of LAVs into drug targets in several areas. These included (1) the initiation and better use of cohorts with multi-omics profiling on the participants; (2) the generation of longitudinal information on multiple individuals; (3) the collection of data from non-human species (both long and short-lived) for comparative biology studies; (4) the refinement of computational tools for integrative analyses; (5) the development of novel computational and statistical inference techniques for assessing the potential of a drug target; (6) the identification of available drugs that could modulate a target in a way that could potentially provide protection against age-related diseases and/or enhance longevity; and (7) the development or enhancement of databases and repositories of relevant information, such as the Longevity Genomics website ( https://www.longevitygenomics.org ), to enhance and help motivate future interdisciplinary studies. Integrative approaches that examine the influence of LAVs on molecular physiologic phenotypes that might be amenable to pharmacological modulation are necessary for translating LAVs into drugs to enhance health and life span.
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http://dx.doi.org/10.1007/s11357-018-0046-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6294726PMC
December 2018

Accelerating the Drug Delivery Pipeline for Acute and Chronic Pancreatitis: Summary of the Working Group on Drug Development and Trials in Recurrent Acute Pancreatitis at the National Institute of Diabetes and Digestive and Kidney Diseases Workshop.

Pancreas 2018 Nov/Dec;47(10):1193-1199

Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA.

Recurrent acute pancreatitis (RAP) is a complex clinical syndrome with significant morbidity, unpredictable outcomes, and limited treatment options. The National Institute of Diabetes and Digestive and Kidney Disease sponsored a workshop on July 25, 2018, in Pittsburgh, Pennsylvania, to address research gaps impeding development of effective therapies for pancreatitis. The RAP working group identified challenges to clinical progress using existing definitions, risk assessment, diagnostic and severity criteria, disease trajectories, outcomes, and research methods. Recurrent acute pancreatitis includes all the risk of acute pancreatitis and often progresses to chronic pancreatitis with variable complications of chronic pain, exocrine insufficiency, diabetes, and pancreatic cancer. However, the great variability among individuals with RAP requires better precision in defining the risks, individual episodes, as well as their frequency, pathogenic pathways, and specific outcome measures for each of the systems affected by pancreatic inflammation. Because of disease complexity, few patients are similar enough for traditional studies and methods to conduct clinical trials with small sample sizes are required. The need for genetic testing, biomarker development, and better imaging methods was highlighted. Adaptive and N-of-one study designs, better endpoints, and outcome measures including patient-reported outcomes should considered early in developing future therapeutic trial design and include all stakeholders.
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http://dx.doi.org/10.1097/MPA.0000000000001164DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195328PMC
March 2019

Exome-wide analysis of bi-allelic alterations identifies a Lynch phenotype in The Cancer Genome Atlas.

Genome Med 2018 09 14;10(1):69. Epub 2018 Sep 14.

Human Biology Program, J. Craig Venter Institute, La Jolla, CA, USA.

Background: Cancer susceptibility germline variants generally require somatic alteration of the remaining allele to drive oncogenesis and, in some cases, tumor mutational profiles. Whether combined germline and somatic bi-allelic alterations are universally required for germline variation to influence tumor mutational profile is unclear. Here, we performed an exome-wide analysis of the frequency and functional effect of bi-allelic alterations in The Cancer Genome Atlas (TCGA).

Methods: We integrated germline variant, somatic mutation, somatic methylation, and somatic copy number loss data from 7790 individuals from TCGA to identify germline and somatic bi-allelic alterations in all coding genes. We used linear models to test for association between mono- and bi-allelic alterations and somatic microsatellite instability (MSI) and somatic mutational signatures.

Results: We discovered significant enrichment of bi-allelic alterations in mismatch repair (MMR) genes and identified six bi-allelic carriers with elevated MSI, consistent with Lynch syndrome. In contrast, we find little evidence of an effect of mono-allelic germline variation on MSI. Using MSI burden and bi-allelic alteration status, we reclassify two variants of unknown significance in MSH6 as potentially pathogenic for Lynch syndrome. Extending our analysis of MSI to a set of 127 DNA damage repair (DDR) genes, we identified a novel association between methylation of SHPRH and MSI burden.

Conclusions: We find that bi-allelic alterations are infrequent in TCGA but most frequently occur in BRCA1/2 and MMR genes. Our results support the idea that bi-allelic alteration is required for germline variation to influence tumor mutational profile. Overall, we demonstrate that integrating germline, somatic, and epigenetic alterations provides new understanding of somatic mutational profiles.
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http://dx.doi.org/10.1186/s13073-018-0579-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6138910PMC
September 2018
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