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We have sequenced the complete genomes of 72 individuals affected with early-onset familial Alzheimer's disease caused by an autosomal dominant, highly penetrant mutation in the presenilin-1 (PSEN1) gene, and performed genome-wide association testing to identify variants that modify age at onset (AAO) of Alzheimer's disease. Our analysis identified a haplotype of single-nucleotide polymorphisms (SNPs) on chromosome 17 within a chemokine gene cluster associated with delayed onset of mild-cognitive impairment and dementia. Individuals carrying this haplotype had a mean AAO of mild-cognitive impairment at 51.0±5.2 years compared with 41.1±7.4 years for those without these SNPs. This haplotype thus appears to modify Alzheimer's AAO, conferring a large (∼10 years) protective effect. The associated locus harbors several chemokines including eotaxin-1 encoded by CCL11, and the haplotype includes a missense polymorphism in this gene. Validating this association, we found plasma eotaxin-1 levels were correlated with disease AAO in an independent cohort from the University of California San Francisco Memory and Aging Center. In this second cohort, the associated haplotype disrupted the typical age-associated increase of eotaxin-1 levels, suggesting a complex regulatory role for this haplotype in the general population. Altogether, these results suggest eotaxin-1 as a novel modifier of Alzheimer's disease AAO and open potential avenues for therapy.

Huntington disease (HD) reflects the dominant consequences of a CAG-repeat expansion in HTT. Analysis of common SNP-based haplotypes has revealed that most European HD subjects have distinguishable HTT haplotypes on their normal and disease chromosomes and that ∼50% of the latter share the same major HD haplotype. We reasoned that sequence-level investigation of this founder haplotype could provide significant insights into the history of HD and valuable information for gene-targeting approaches. Consequently, we performed whole-genome sequencing of HD and control subjects from four independent families in whom the major European HD haplotype segregates with the disease. Analysis of the full-sequence-based HTT haplotype indicated that these four families share a common ancestor sufficiently distant to have permitted the accumulation of family-specific variants. Confirmation of new CAG-expansion mutations on this haplotype suggests that unlike most founders of human disease, the common ancestor of HD-affected families with the major haplotype most likely did not have HD. Further, availability of the full sequence data validated the use of SNP imputation to predict the optimal variants for capturing heterozygosity in personalized allele-specific gene-silencing approaches. As few as ten SNPs are capable of revealing heterozygosity in more than 97% of European HD subjects. Extension of allele-specific silencing strategies to the few remaining homozygous individuals is likely to be achievable through additional known SNPs and discovery of private variants by complete sequencing of HTT. These data suggest that the current development of gene-based targeting for HD could be extended to personalized allele-specific approaches in essentially all HD individuals of European ancestry.

As large clinical and multiomics datasets and knowledge resources accumulate, they need to be transformed into computable and actionable information to support automated reasoning. These datasets range from laboratory experiment results to electronic health records (EHRs). Barriers to accessibility and sharing of such datasets include diversity of content, size and privacy. Effective transformation of data into information requires harmonization of stakeholder goals, implementation, enforcement of standards regarding quality and completeness, and availability of resources for maintenance and updates. Systems such as the Biomedical Data Translator leverage knowledge graphs (KGs), structured and machine learning readable knowledge representation, to encode knowledge extracted through inference. We focus here on the transformation of data from multiomics datasets and EHRs into compact knowledge, represented in a KG data structure. We demonstrate this data transformation in the context of the Translator ecosystem, including clinical trials, drug approvals, cancer, wellness, and EHR data. These transformations preserve individual privacy. We provide access to the five resulting KGs through the Translator framework. We show examples of biomedical research questions supported by our KGs, and discuss issues arising from extracting biomedical knowledge from multiomics data., Competing Interests: Competing Interests JH has also received funding (paid to the Institute of Systems Biology) from Bristol Myers Squibb, Gilead, Janssen, Novartis and Pfizer for research unrelated to this study. The other authors declare no conflict of interest.

Aging manifests as progressive deteriorations in homeostasis, requiring systems-level perspectives to investigate the gradual molecular dysregulation of underlying biological processes. Here, we report systemic changes in the molecular regulation of biological processes under multiple lifespan-extending interventions. Differential Rank Conservation (DIRAC) analyses of mouse liver proteomics and transcriptomics data show that mechanistically distinct lifespan-extending interventions (acarbose, 17α-estradiol, rapamycin, and calorie restriction) generally tighten the regulation of biological modules. These tightening patterns are similar across the interventions, particularly in processes such as fatty acid oxidation, immune response, and stress response. Differences in DIRAC patterns between proteins and transcripts highlight specific modules which may be tightened via augmented cap-independent translation. Moreover, the systemic shifts in fatty acid metabolism are supported through integrated analysis of liver transcriptomics data with a mouse genome-scale metabolic model. Our findings highlight the power of systems-level approaches for identifying and characterizing the biological processes involved in aging and longevity., (© 2023. The Author(s).)

Motivation: With the rapidly growing volume of knowledge and data in biomedical databases, improved methods for knowledge-graph-based computational reasoning are needed in order to answer translational questions. Previous efforts to solve such challenging computational reasoning problems have contributed tools and approaches, but progress has been hindered by the lack of an expressive analysis workflow language for translational reasoning and by the lack of a reasoning engine-supporting that language-that federates semantically integrated knowledge-bases., Results: We introduce ARAX, a new reasoning system for translational biomedicine that provides a web browser user interface and an application programming interface (API). ARAX enables users to encode translational biomedical questions and to integrate knowledge across sources to answer the user's query and facilitate exploration of results. For ARAX, we developed new approaches to query planning, knowledge-gathering, reasoning and result ranking and dynamically integrate knowledge providers for answering biomedical questions. To illustrate ARAX's application and utility in specific disease contexts, we present several use-case examples., Availability and Implementation: The source code and technical documentation for building the ARAX server-side software and its built-in knowledge database are freely available online (https://github.com/RTXteam/RTX). We provide a hosted ARAX service with a web browser interface at arax.rtx.ai and a web API endpoint at arax.rtx.ai/api/arax/v1.3/ui/., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2023. Published by Oxford University Press.)

Background: Comprehensive treatment of Alzheimer's disease and related dementias (ADRD) requires not only pharmacologic treatment but also management of existing medical conditions and lifestyle modifications including diet, cognitive training, and exercise. Personalized, multimodal therapies are needed to best prevent and treat Alzheimer's disease (AD)., Objective: The Coaching for Cognition in Alzheimer's (COCOA) trial was a prospective randomized controlled trial to test the hypothesis that a remotely coached multimodal lifestyle intervention would improve early-stage AD., Methods: Participants with early-stage AD were randomized into two arms. Arm 1 (N = 24) received standard of care. Arm 2 (N = 31) additionally received telephonic personalized coaching for multiple lifestyle interventions. The primary outcome was a test of the hypothesis that the Memory Performance Index (MPI) change over time would be better in the intervention arm than in the control arm. The Functional Assessment Staging Test was assessed for a secondary outcome. COCOA collected psychometric, clinical, lifestyle, genomic, proteomic, metabolomic, and microbiome data at multiple timepoints (dynamic dense data) across two years for each participant., Results: The intervention arm ameliorated 2.1 [1.0] MPI points (mean [SD], p = 0.016) compared to the control over the two-year intervention. No important adverse events or side effects were observed., Conclusion: Multimodal lifestyle interventions are effective for ameliorating cognitive decline and have a larger effect size than pharmacological interventions. Dietary changes and exercise are likely to be beneficial components of multimodal interventions in many individuals. Remote coaching is an effective intervention for early stage ADRD. Remote interventions were effective during the COVID pandemic.

Background: A carbohydrate-restricted diet aimed at lowering insulin levels has the potential to slow Alzheimer's disease (AD). Restricting carbohydrate consumption reduces insulin resistance, which could improve glucose uptake and neural health. A hallmark feature of AD is widespread cortical thinning; however, no study has demonstrated that lower net carbohydrate (nCHO) intake is linked to attenuated cortical atrophy in patients with AD and confirmed amyloidosis., Objective: We tested the hypothesis that individuals with AD and confirmed amyloid burden eating a carbohydrate-restricted diet have thicker cortex than those eating a moderate-to-high carbohydrate diet., Methods: A total of 31 patients (mean age 71.4±7.0 years) with AD and confirmed amyloid burden were divided into two groups based on a 130 g/day nCHO cutoff. Cortical thickness was estimated from T1-weighted MRI using FreeSurfer. Cortical surface analyses were corrected for multiple comparisons using cluster-wise probability. We assessed group differences using a two-tailed two-independent sample t-test. Linear regression analyses using nCHO as a continuous variable, accounting for confounders, were also conducted., Results: The lower nCHO group had significantly thicker cortex within somatomotor and visual networks. Linear regression analysis revealed that lower nCHO intake levels had a significant association with cortical thickness within the frontoparietal, cingulo-opercular, and visual networks., Conclusions: Restricting carbohydrates may be associated with reduced atrophy in patients with AD. Lowering nCHO to under 130 g/day would allow patients to follow the well-validated MIND diet while benefiting from lower insulin levels.

Recovery from COVID-19 is associated with production of anti-SARS-CoV-2 antibodies, but it is uncertain whether these confer immunity. We describe viral RNA shedding duration in hospitalized patients and identify patients with recurrent shedding. We sequenced viruses from two distinct episodes of symptomatic COVID-19 separated by 144 days in a single patient, to conclusively describe reinfection with a different strain harboring the spike variant D614G. This case of reinfection was one of the first cases of reinfection reported in 2020. With antibody, B cell and T cell analytics, we show correlates of adaptive immunity at reinfection, including a differential response in neutralizing antibodies to a D614G pseudovirus. Finally, we discuss implications for vaccine programs and begin to define benchmarks for protection against reinfection from SARS-CoV-2.

Background: Biomedical translational science is increasingly using computational reasoning on repositories of structured knowledge (such as UMLS, SemMedDB, ChEMBL, Reactome, DrugBank, and SMPDB in order to facilitate discovery of new therapeutic targets and modalities. The NCATS Biomedical Data Translator project is working to federate autonomous reasoning agents and knowledge providers within a distributed system for answering translational questions. Within that project and the broader field, there is a need for a framework that can efficiently and reproducibly build an integrated, standards-compliant, and comprehensive biomedical knowledge graph that can be downloaded in standard serialized form or queried via a public application programming interface (API)., Results: To create a knowledge provider system within the Translator project, we have developed RTX-KG2, an open-source software system for building-and hosting a web API for querying-a biomedical knowledge graph that uses an Extract-Transform-Load approach to integrate 70 knowledge sources (including the aforementioned core six sources) into a knowledge graph with provenance information including (where available) citations. The semantic layer and schema for RTX-KG2 follow the standard Biolink model to maximize interoperability. RTX-KG2 is currently being used by multiple Translator reasoning agents, both in its downloadable form and via its SmartAPI-registered interface. Serializations of RTX-KG2 are available for download in both the pre-canonicalized form and in canonicalized form (in which synonyms are merged). The current canonicalized version (KG2.7.3) of RTX-KG2 contains 6.4M nodes and 39.3M edges with a hierarchy of 77 relationship types from Biolink., Conclusion: RTX-KG2 is the first knowledge graph that integrates UMLS, SemMedDB, ChEMBL, DrugBank, Reactome, SMPDB, and 64 additional knowledge sources within a knowledge graph that conforms to the Biolink standard for its semantic layer and schema. RTX-KG2 is publicly available for querying via its API at arax.rtx.ai/api/rtxkg2/v1.2/openapi.json . The code to build RTX-KG2 is publicly available at github:RTXteam/RTX-KG2 ., (© 2022. The Author(s).)

Bipolar disorder is an often-severe mental health condition characterized by alternation between extreme mood states of mania and depression. Despite strong heritability and the recent identification of 64 common variant risk loci of small effect, pathophysiological mechanisms remain unknown. Here, we analyzed genome sequences from 41 multiply-affected pedigrees and identified variants in 741 genes with nominally significant linkage or association with bipolar disorder. These 741 genes overlapped known risk genes for neurodevelopmental disorders and clustered within gene networks enriched for synaptic and nuclear functions. The top variant in this analysis - prioritized by statistical association, predicted deleteriousness, and network centrality - was a missense variant in the gene encoding D-amino acid oxidase (DAO G131V ). Heterologous expression of DAO G131V in human cells resulted in decreased DAO protein abundance and enzymatic activity. In a knock-in mouse model of DAO G131 , Dao G130V/+ , we similarly found decreased DAO protein abundance in hindbrain regions, as well as enhanced stress susceptibility and blunted behavioral responses to pharmacological inhibition of N-methyl-D-aspartate receptors (NMDARs). RNA sequencing of cerebellar tissue revealed that Dao G130V resulted in decreased expression of two gene networks that are enriched for synaptic functions and for genes expressed, respectively, in Purkinje neurons or granule neurons. These gene networks were also down-regulated in the cerebellum of patients with bipolar disorder compared to healthy controls and were enriched for additional rare variants associated with bipolar disorder risk. These findings implicate dysregulation of NMDAR signaling and of gene expression in cerebellar neurons in bipolar disorder pathophysiology and provide insight into its genetic architecture., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Comprehensive treatment of Alzheimer's disease (AD) requires not only pharmacologic treatment but also management of existing medical conditions and lifestyle modifications including diet, cognitive training, and exercise. We present the design and methodology for the Coaching for Cognition in Alzheimer's (COCOA) trial. AD and other dementias result from the interplay of multiple interacting dysfunctional biological systems. Monotherapies have had limited success. More interventional studies are needed to test the effectiveness of multimodal multi-domain therapies for dementia prevention and treatment. Multimodal therapies use multiple interventions to address multiple systemic causes and potentiators of cognitive decline and functional loss; they can be personalized, as different sets of etiologies and systems responsive to therapy may be present in different individuals. COCOA is designed to test the hypothesis that coached multimodal interventions beneficially alter the trajectory of cognitive decline for individuals on the spectrum of AD and related dementias (ADRD). COCOA is a two-arm prospective randomized controlled trial (RCT). COCOA collects psychometric, clinical, lifestyle, genomic, proteomic, metabolomic, and microbiome data at multiple timepoints across 2 years for each participant. These data enable systems biology analyses. One arm receives standard of care and generic healthy aging recommendations. The other arm receives standard of care and personalized data-driven remote coaching. The primary outcome measure is the Memory Performance Index (MPI), a measure of cognition. The MPI is a summary statistic of the MCI Screen (MCIS). Secondary outcome measures include the Functional Assessment Staging Test (FAST), a measure of function. COCOA began enrollment in January 2018. We hypothesize that multimodal interventions will ameliorate cognitive decline and that data-driven health coaching will increase compliance, assist in personalizing multimodal interventions, and improve outcomes for patients, particularly for those in the early stages of the AD spectrum., Highlights: The Coaching for Cognition in Alzheimer's (COCOA) trial tests personalized multimodal lifestyle interventions for Alzheimer's disease and related dementias.Dense longitudinal molecular data will be useful for future studies.Increased use of Hill's criteria in analyses may advance knowledge generation.Remote coaching may be an effective intervention.Because lifestyle interventions are inexpensive, they may be particularly valuable in reducing global socioeconomic disparities in dementia care., Competing Interests: Drs. Shankle and Hara are employees of EMBIC Corporation. There are no other conflicts of interest for any of the authors. Author disclosures are available in the supporting information., (© 2022 The Authors. Alzheimer's & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Competing Interests: The authors have no conflicts of interest.

Projections of the near future of daily case incidence of COVID-19 are valuable for informing public policy. Near-future estimates are also useful for outbreaks of other diseases. Short-term predictions are unlikely to be affected by changes in herd immunity. In the absence of major net changes in factors that affect reproduction number (R), the two-parameter exponential model should be a standard model - indeed, it has been standard for epidemiological analysis of pandemics for a century but in recent decades has lost popularity to more complex compartmental models. Exponential models should be routinely included in reports describing epidemiological models as a reference, or null hypothesis. Exponential models should be fitted separately for each epidemiologically distinct jurisdiction. They should also be fitted separately to time intervals that differ by any major changes in factors that affect R. Using an exponential model, incidence-count half-life ( t 1/2 ) is a better statistic than R. Here an example of the exponential model is applied to King County, Washington during Spring 2020. During the pandemic, the parameters and predictions of this model have remained stable for intervals of one to four months, and the accuracy of model predictions has outperformed models with more parameters. The COVID pandemic can be modeled as a series of exponential curves, each spanning an interval ranging from one to four months. The length of these intervals is hard to predict, other than to extrapolate that future intervals will last about as long as past intervals., Competing Interests: Conflicts of Interest None declared.

Introduction: There is an urgent need to develop effective interventional treatments for people with Alzheimer's disease (AD). AD results from a complex multi-decade interplay of multiple interacting dysfunctional biological systems that have not yet been fully elucidated. Epidemiological studies have linked several modifiable lifestyle factors with increased incidence for AD. Because monotherapies have failed to prevent or ameliorate AD, interventional studies should deploy multiple, targeted interventions that address the dysfunctional systems that give rise to AD., Methods: This randomized controlled trial (RCT) will examine the efficacy of a 12-month personalized, multimodal, lifestyle intervention in 60 mild cognitive impairment (MCI) and early stage AD patients (aged 50+, amyloid positivity). Both groups receive data-driven, lifestyle recommendations designed to target multiple systemic pathways implicated in AD. One group receives these personalized recommendations without coaching. The other group receives personalized recommendations with health coaching, dietary counseling, exercise training, cognitive stimulation, and nutritional supplements. We collect clinical, proteomic, metabolomic, neuroimaging, and genetic data to fuel systems-biology analyses. We will examine effects on cognition and hippocampal volume. The overarching goal of the study is to longitudinally track biological systems implicated in AD to reveal the dynamics between these systems during the intervention to understand differences in treatment response., Results: We have developed and implemented a protocol for a personalized, multimodal intervention program for early AD patients. We began enrollment in September 2019; we have enrolled a third of our target (20 of 60) with a 95% retention and 86% compliance rate., Discussion: This study presents a paradigm shift in designing multimodal, lifestyle interventions to reduce cognitive decline, and how to elucidate the biological systems being targeted. Analytical efforts to explain mechanistic or causal underpinnings of individual trajectories and the interplay between multi-omic variables will inform the design of future hypotheses and development of effective precision medicine trials., Competing Interests: None., (© 2021 The Authors. Alzheimer's & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.)

We report a case of a patient with mixed dementia successfully treated with a personalized multimodal therapy. Monotherapeutics are inadequate for the treatment of Alzheimer's disease (AD) and mixed dementia; therefore, we approach treatment through an adaptive personalized multimodal program. Many multimodal programs are pre-determined, and thus may not address the underlying contributors to cognitive decline in each particular individual. The combination of a targeted, personalized, precision medicine approach using a multimodal program promises advantages over monotherapies and untargeted multimodal therapies for multifactorial dementia. In this case study, we describe successful treatment for a patient diagnosed with AD, using a multimodal, programmatic, precision medicine intervention encompassing therapies targeting multiple dementia diastheses. We describe specific interventions used in this case that are derived from a comprehensive protocol for AD precision medicine. After treatment, our patient demonstrated improvements in quantitative neuropsychological testing, volumetric neuroimaging, PET scans, and serum chemistries, accompanied by symptomatic improvement over a 3.5-year period. This case outcome supports the need for rigorous trials of comprehensive, targeted combination therapies to stabilize, restore, and prevent cognitive decline in individuals with potentially many underlying causes of such decline and dementia. Our multimodal therapy included personalized treatments to address each potential perturbation to neuroplasticity. In particular, neuroinflammation and metabolic subsystems influence cognitive function and hippocampal volume. In this patient with a primary biliary cholangitis (PBC) multimorbidity component, we introduced a personalized diet that helped reduce liver inflammation. Together, all these components of multimodal therapy showed a sustained functional and cognitive benefit. Multimodal therapies may have systemwide benefits on all dementias, particularly in the context of multimorbidity. Furthermore, these therapies provide generalized health benefits, as many of the factors - such as inflammation - that impact cognitive function also impact other systems., Competing Interests: Conflicts of Interest The authors have no conflicts of interest to declare.

Recovery from COVID-19 is associated with production of anti-SARS-CoV-2 antibodies, but it is uncertain whether these confer immunity. We describe viral RNA shedding duration in hospitalized patients and identify patients with recurrent shedding. We sequenced viruses from two distinct episodes of symptomatic COVID-19 separated by 144 days in a single patient, to conclusively describe reinfection with a new strain harboring the spike variant D614G. With antibody and B cell analytics, we show correlates of adaptive immunity, including a differential response to D614G. Finally, we discuss implications for vaccine programs and begin to define benchmarks for protection against reinfection from SARS-CoV-2.

Preterm birth (PTB) complications are the leading cause of long-term morbidity and mortality in children. By using whole blood samples, we integrated whole-genome sequencing (WGS), RNA sequencing (RNA-seq), and DNA methylation data for 270 PTB and 521 control families. We analyzed this combined dataset to identify genomic variants associated with PTB and secondary analyses to identify variants associated with very early PTB (VEPTB) as well as other subcategories of disease that may contribute to PTB. We identified differentially expressed genes (DEGs) and methylated genomic loci and performed expression and methylation quantitative trait loci analyses to link genomic variants to these expression and methylation changes. We performed enrichment tests to identify overlaps between new and known PTB candidate gene systems. We identified 160 significant genomic variants associated with PTB-related phenotypes. The most significant variants, DEGs, and differentially methylated loci were associated with VEPTB. Integration of all data types identified a set of 72 candidate biomarker genes for VEPTB, encompassing genes and those previously associated with PTB. Notably, PTB-associated genes RAB31 and RBPJ were identified by all three data types (WGS, RNA-seq, and methylation). Pathways associated with VEPTB include EGFR and prolactin signaling pathways, inflammation- and immunity-related pathways, chemokine signaling, IFN-γ signaling, and Notch1 signaling. Progress in identifying molecular components of a complex disease is aided by integrated analyses of multiple molecular data types and clinical data. With these data, and by stratifying PTB by subphenotype, we have identified associations between VEPTB and the underlying biology., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

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., (Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.)

In the version of this article published, the P values for the enrichment of single mutation categories were inadvertently not corrected for multiple testing. After multiple-testing correction, only two of the six mutation categories mentioned are still statistically significant. To reflect this, the text "More specifically, paternally derived DNMs are enriched in transitions in A[.]G contexts, especially ACG>ATG and ATG>ACG (Bonferroni-corrected P = 1.3 × 10 -2 and P = 1 × 10 -3 , respectively). Additionally, we observed overrepresentation of ATA>ACA mutations (Bonferroni-corrected P = 4.28 × 10 -2 ) for DNMs of paternal origin. Among maternally derived DNMs, CCA>CTA, GCA>GTA and TCT>TGT mutations were significantly overrepresented (Bonferroni-corrected P = 4 × 10 -4 , P = 5 × 10 -4 , P = 1 × 10 -3 , respectively)" should read "More specifically, CCA>CTA and GCA>GTA mutations were significantly overenriched on the maternal allele (Bonferroni-corrected P = 0.0192 and P = 0.048, respectively)." Additionally, the last sentence to the legend for Fig. 3b should read "Green boxes highlight the mutation categories that differ significantly" instead of "Green boxes highlight the mutation categories that differ more than 1% of mutation load with a bootstrapping P value <0.05." Corrected versions of Fig. 3b and Supplementary Table 25 appear with the Author Correction.

Modifiers of Mendelian disorders can provide insights into disease mechanisms and guide therapeutic strategies. A recent genome-wide association (GWA) study discovered genetic modifiers of Huntington's disease (HD) onset in Europeans. Here, we performed whole genome sequencing and GWA analysis of a Venezuelan HD cluster whose families were crucial for the original mapping of the HD gene defect. The Venezuelan HD subjects develop motor symptoms earlier than their European counterparts, implying the potential for population-specific modifiers. The main Venezuelan HD family inherits HTT haplotype hap.03, which differs subtly at the sequence level from European HD hap.03, suggesting a different ancestral origin but not explaining the earlier age at onset in these Venezuelans. GWA analysis of the Venezuelan HD cluster suggests both population-specific and population-shared genetic modifiers. Genome-wide significant signals at 7p21.2-21.1 and suggestive association signals at 4p14 and 17q21.2 are evident only in Venezuelan HD, but genome-wide significant association signals at the established European chromosome 15 modifier locus are improved when Venezuelan HD data are included in the meta-analysis. Venezuelan-specific association signals on chromosome 7 center on SOSTDC1, which encodes a bone morphogenetic protein antagonist. The corresponding SNPs are associated with reduced expression of SOSTDC1 in non-Venezuelan tissue samples, suggesting that interaction of reduced SOSTDC1 expression with a population-specific genetic or environmental factor may be responsible for modification of HD onset in Venezuela. Detection of population-specific modification in Venezuelan HD supports the value of distinct disease populations in revealing novel aspects of a disease and population-relevant therapeutic strategies., Competing Interests: The authors have declared that no competing interests exist.

Genotype imputation is a powerful strategy for achieving the large sample sizes required for identification of variants underlying complex phenotypes, but imputation of rare variants remains problematic. Genetically isolated populations offer one solution, however population-specific reference panels are needed to assure optimal imputation accuracy and allele frequency estimation. Here we report the Anabaptist Genome Reference Panel (AGRP), the first whole-genome catalogue of variants and phased haplotypes in people of Amish and Mennonite ancestry. Based on high-depth whole-genome sequence (WGS) from 265 individuals, the AGRP contains >12 M high-confidence single nucleotide variants and short indels, of which ~12.5% are novel. These Anabaptist-specific variants were more deleterious than variants with comparable frequencies observed in the 1000 Genomes panel. About 43,000 variants showed enriched allele frequencies in AGRP, consistent with drift. When combined with the 1000 Genomes Project reference panel, the AGRP substantially improved imputation, especially for rarer variants. The AGRP is freely available to researchers through an imputation server.

The indigenous people of the Tibetan Plateau have been the subject of much recent interest because of their unique genetic adaptations to high altitude. Recent studies have demonstrated that the Tibetan EPAS1 haplotype is involved in high altitude-adaptation and originated in an archaic Denisovan-related population. We sequenced the whole-genomes of 27 Tibetans and conducted analyses to infer a detailed history of demography and natural selection of this population. We detected evidence of population structure between the ancestral Han and Tibetan subpopulations as early as 44 to 58 thousand years ago, but with high rates of gene flow until approximately 9 thousand years ago. The CMS test ranked EPAS1 and EGLN1 as the top two positive selection candidates, and in addition identified PTGIS, VDR, and KCTD12 as new candidate genes. The advantageous Tibetan EPAS1 haplotype shared many variants with the Denisovan genome, with an ancient gene tree divergence between the Tibetan and Denisovan haplotypes of about 1 million years ago. With the exception of EPAS1, we observed no evidence of positive selection on Denisovan-like haplotypes.

De novo mutations (DNMs) originating in gametogenesis are an important source of genetic variation. We use a data set of 7,216 autosomal DNMs with resolved parent of origin from whole-genome sequencing of 816 parent-offspring trios to investigate differences between maternally and paternally derived DNMs and study the underlying mutational mechanisms. Our results show that the number of DNMs in offspring increases not only with paternal age, but also with maternal age, and that some genome regions show enrichment for maternally derived DNMs. We identify parent-of-origin-specific mutation signatures that become more pronounced with increased parental age, pointing to different mutational mechanisms in spermatogenesis and oogenesis. Moreover, we find DNMs that are spatially clustered to have a unique mutational signature with no significant differences between parental alleles, suggesting a different mutational mechanism. Our findings provide insights into the molecular mechanisms that underlie mutagenesis and are relevant to disease and evolution in humans.

Currently, the best clinical predictor for inflammatory bowel disease (IBD) is family history. Over 163 sequence variants have been associated with IBD in genome-wide association studies, but they have weak effects and explain only a fraction of the observed heritability. It is expected that additional variants contribute to the genomic architecture of IBD, possibly including rare variants with effect sizes larger than the identified common variants. Here we applied a family study design and sequenced 38 individuals from five families, under the hypothesis that families with multiple IBD-affected individuals harbor one or more risk variants that (i) are shared among affected family members, (ii) are rare and (iii) have substantial effect on disease development. Our analysis revealed not only novel candidate risk variants but also high polygenic risk scores for common known risk variants in four out of the five families. Functional analysis of our top novel variant in the remaining family, a rare missense mutation in the ubiquitin ligase TRIM11, suggests that it leads to increased nuclear factor of kappa light chain enhancer in B-cells (NF-κB) signaling. We conclude that an accumulation of common weak-effect variants accounts for the high incidence of IBD in most, but not all families we analyzed and that a family study design can identify novel rare variants conferring risk for IBD with potentially large effect size, such as the TRIM11 p.H414Y mutation.

Adams-Oliver syndrome (AOS) is a rare developmental disorder characterized by the presence of aplasia cutis congenita (ACC) of the scalp vertex and terminal limb-reduction defects. Cardiovascular anomalies are also frequently observed. Mutations in five genes have been identified as a cause for AOS prior to this report. Mutations in EOGT and DOCK6 cause autosomal-recessive AOS, whereas mutations in ARHGAP31, RBPJ, and NOTCH1 lead to autosomal-dominant AOS. Because RBPJ, NOTCH1, and EOGT are involved in NOTCH signaling, we hypothesized that mutations in other genes involved in this pathway might also be implicated in AOS pathogenesis. Using a candidate-gene-based approach, we prioritized DLL4, a critical NOTCH ligand, due to its essential role in vascular development in the context of cardiovascular features in AOS-affected individuals. Targeted resequencing of the DLL4 gene with a custom enrichment panel in 89 independent families resulted in the identification of seven mutations. A defect in DLL4 was also detected in two families via whole-exome or genome sequencing. In total, nine heterozygous mutations in DLL4 were identified, including two nonsense and seven missense variants, the latter encompassing four mutations that replace or create cysteine residues, which are most likely critical for maintaining structural integrity of the protein. Affected individuals with DLL4 mutations present with variable clinical expression with no emerging genotype-phenotype correlations. Our findings demonstrate that DLL4 mutations are an additional cause of autosomal-dominant AOS or isolated ACC and provide further evidence for a key role of NOTCH signaling in the etiology of this disorder., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Mutations in ATP1A3 cause Alternating Hemiplegia of Childhood (AHC) by disrupting function of the neuronal Na+/K+ ATPase. Published studies to date indicate 2 recurrent mutations, D801N and E815K, and a more severe phenotype in the E815K cohort. We performed mutation analysis and retrospective genotype-phenotype correlations in all eligible patients with AHC enrolled in the US AHC Foundation registry from 1997-2012. Clinical data were abstracted from standardized caregivers' questionnaires and medical records and confirmed by expert clinicians. We identified ATP1A3 mutations by Sanger and whole genome sequencing, and compared phenotypes within and between 4 groups of subjects, those with D801N, E815K, other ATP1A3 or no ATP1A3 mutations. We identified heterozygous ATP1A3 mutations in 154 of 187 (82%) AHC patients. Of 34 unique mutations, 31 (91%) are missense, and 16 (47%) had not been previously reported. Concordant with prior studies, more than 2/3 of all mutations are clusteredin exons 17 and 18. Of 143 simplex occurrences, 58 had D801N (40%), 38 had E815K(26%) and 11 had G947R (8%) mutations [corrected].Patients with an E815K mutation demonstrate an earlier age of onset, more severe motor impairment and a higher prevalence of status epilepticus. This study further expands the number and spectrum of ATP1A3 mutations associated with AHC and confirms a more deleterious effect of the E815K mutation on selected neurologic outcomes. However, the complexity of the disorder and the extensive phenotypic variability among subgroups merits caution and emphasizes the need for further studies.

We sequenced the genomes of 200 individuals from 41 families multiply affected with bipolar disorder (BD) to identify contributions of rare variants to genetic risk. We initially focused on 3,087 candidate genes with known synaptic functions or prior evidence from genome-wide association studies. BD pedigrees had an increased burden of rare variants in genes encoding neuronal ion channels, including subunits of GABAA receptors and voltage-gated calcium channels. Four uncommon coding and regulatory variants also showed significant association, including a missense variant in GABRA6. Targeted sequencing of 26 of these candidate genes in an additional 3,014 cases and 1,717 controls confirmed rare variant associations in ANK3, CACNA1B, CACNA1C, CACNA1D, CACNG2, CAMK2A, and NGF. Variants in promoters and 5' and 3' UTRs contributed more strongly than coding variants to risk for BD, both in pedigrees and in the case-control cohort. The genes and pathways identified in this study regulate diverse aspects of neuronal excitability. We conclude that rare variants in neuronal excitability genes contribute to risk for BD.

The identification of DNA copy numbers from short-read sequencing data remains a challenge for both technical and algorithmic reasons. The raw data for these analyses are measured in tens to hundreds of gigabytes per genome; transmitting, storing, and analyzing such large files is cumbersome, particularly for methods that analyze several samples simultaneously. We developed a very efficient representation of depth of coverage (150-1000× compression) that enables such analyses. Current methods for analyzing variants in whole-genome sequencing (WGS) data frequently miss copy number variants (CNVs), particularly hemizygous deletions in the 1-100 kb range. To fill this gap, we developed a method to identify CNVs in individual genomes, based on comparison to joint profiles pre-computed from a large set of genomes. We analyzed depth of coverage in over 6000 high quality (>40×) genomes. The depth of coverage has strong sequence-specific fluctuations only partially explained by global parameters like %GC. To account for these fluctuations, we constructed multi-genome profiles representing the observed or inferred diploid depth of coverage at each position along the genome. These Reference Coverage Profiles (RCPs) take into account the diverse technologies and pipeline versions used. Normalization of the scaled coverage to the RCP followed by hidden Markov model (HMM) segmentation enables efficient detection of CNVs and large deletions in individual genomes. Use of pre-computed multi-genome coverage profiles improves our ability to analyze each individual genome. We make available RCPs and tools for performing these analyses on personal genomes. We expect the increased sensitivity and specificity for individual genome analysis to be critical for achieving clinical-grade genome interpretation.

Febrile seizures affect 2-4% of all children and have a strong genetic component. Recurrent mutations in three main genes (SCN1A, SCN1B and GABRG2) have been identified that cause febrile seizures with or without epilepsy. Here we report the identification of mutations in STX1B, encoding syntaxin-1B, that are associated with both febrile seizures and epilepsy. Whole-exome sequencing in independent large pedigrees identified cosegregating STX1B mutations predicted to cause an early truncation or an in-frame insertion or deletion. Three additional nonsense or missense mutations and a de novo microdeletion encompassing STX1B were then identified in 449 familial or sporadic cases. Video and local field potential analyses of zebrafish larvae with antisense knockdown of stx1b showed seizure-like behavior and epileptiform discharges that were highly sensitive to increased temperature. Wild-type human syntaxin-1B but not a mutated protein rescued the effects of stx1b knockdown in zebrafish. Our results thus implicate STX1B and the presynaptic release machinery in fever-associated epilepsy syndromes.

Supercentenarians (110 years or older) are the world's oldest people. Seventy four are alive worldwide, with twenty two in the United States. We performed whole-genome sequencing on 17 supercentenarians to explore the genetic basis underlying extreme human longevity. We found no significant evidence of enrichment for a single rare protein-altering variant or for a gene harboring different rare protein altering variants in supercentenarian compared to control genomes. We followed up on the gene most enriched for rare protein-altering variants in our cohort of supercentenarians, TSHZ3, by sequencing it in a second cohort of 99 long-lived individuals but did not find a significant enrichment. The genome of one supercentenarian had a pathogenic mutation in DSC2, known to predispose to arrhythmogenic right ventricular cardiomyopathy, which is recommended to be reported to this individual as an incidental finding according to a recent position statement by the American College of Medical Genetics and Genomics. Even with this pathogenic mutation, the proband lived to over 110 years. The entire list of rare protein-altering variants and DNA sequence of all 17 supercentenarian genomes is available as a resource to assist the discovery of the genetic basis of extreme longevity in future studies.

Adams-Oliver syndrome (AOS) is a rare malformation syndrome characterized by the presence of two anomalies: aplasia cutis congenita of the scalp and transverse terminal limb defects. Many affected individuals also have additional malformations, including a variety of intracranial anomalies such as periventricular calcification in keeping with cerebrovascular microbleeds, impaired neuronal migration, epilepsy, and microcephaly. Cardiac malformations can be present, as can vascular dysfunction in the forms of cutis marmorata telangiectasia congenita, pulmonary vein stenoses, and abnormal hepatic microvasculature. Elucidated genetic causes include four genes in different pathways, leading to a model of AOS as a multi-pathway disorder. We identified an infant with mild aplasia cutis congenita and terminal transverse limb defects, developmental delay and a severe, diffuse angiopathy with incomplete microvascularization. Whole-genome sequencing documented two rare truncating variants in DOCK6, a gene associated with a type of autosomal recessive AOS that recurrently features periventricular calcification and impaired neurodevelopment. We highlight an unexpectedly high frequency of likely deleterious mutations in this gene in the general population, relative to the rarity of the disease, and discuss possible explanations for this discrepancy., (© 2014 Wiley Periodicals, Inc.)

Background: A mutation in presenilin 1 (E280A) causes early-onset Alzheimer's disease. Understanding the origin of this mutation will inform medical genetics., Methods: We sequenced the genomes of 102 individuals from Antioquia, Colombia. We applied identity-by-descent analysis to identify regions of common ancestry. We estimated the age of the E280A mutation and the local ancestry of the haplotype harboring this mutation., Results: All affected individuals share a minimal haplotype of 1.8 Mb containing E280A. We estimate a time to most recent common ancestor of E280A of 10 (95% credible interval, 7.2-12.6) generations. We date the de novo mutation event to 15 (95% credible interval, 11-25) generations ago. We infer a western European geographic origin of the shared haplotype., Conclusions: The age and geographic origin of E280A are consistent with a single founder dating from the time of the Spanish Conquistadors who began colonizing Colombia during the early 16th century., (Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Genomic information reported as haplotypes rather than genotypes will be increasingly important for personalized medicine. Current technologies generate diploid sequence data that is rarely resolved into its constituent haplotypes. Furthermore, paradigms for thinking about genomic information are based on interpreting genotypes rather than haplotypes. Nevertheless, haplotypes have historically been useful in contexts ranging from population genetics to disease-gene mapping efforts. The main approaches for phasing genomic sequence data are molecular haplotyping, genetic haplotyping, and population-based inference. Long-read sequencing technologies are enabling longer molecular haplotypes, and decreases in the cost of whole-genome sequencing are enabling the sequencing of whole-chromosome genetic haplotypes. Hybrid approaches combining high-throughput short-read assembly with strategic approaches that enable physical or virtual binning of reads into haplotypes are enabling multi-gene haplotypes to be generated from single individuals. These techniques can be further combined with genetic and population approaches. Here, we review advances in whole-genome haplotyping approaches and discuss the importance of haplotypes for genomic medicine. Clinical applications include diagnosis by recognition of compound heterozygosity and by phasing regulatory variation to coding variation. Haplotypes, which are more specific than less complex variants such as single nucleotide variants, also have applications in prognostics and diagnostics, in the analysis of tumors, and in typing tissue for transplantation. Future advances will include technological innovations, the application of standard metrics for evaluating haplotype quality, and the development of databases that link haplotypes to disease.

Notch signaling determines and reinforces cell fate in bilaterally symmetric multicellular eukaryotes. Despite the involvement of Notch in many key developmental systems, human mutations in Notch signaling components have mainly been described in disorders with vascular and bone effects. Here, we report five heterozygous NOTCH1 variants in unrelated individuals with Adams-Oliver syndrome (AOS), a rare disease with major features of aplasia cutis of the scalp and terminal transverse limb defects. Using whole-genome sequencing in a cohort of 11 families lacking mutations in the four genes with known roles in AOS pathology (ARHGAP31, RBPJ, DOCK6, and EOGT), we found a heterozygous de novo 85 kb deletion spanning the NOTCH1 5' region and three coding variants (c.1285T>C [p.Cys429Arg], c.4487G>A [p.Cys1496Tyr], and c.5965G>A [p.Asp1989Asn]), two of which are de novo, in four unrelated probands. In a fifth family, we identified a heterozygous canonical splice-site variant (c.743-1 G>T) in an affected father and daughter. These variants were not present in 5,077 in-house control genomes or in public databases. In keeping with the prominent developmental role described for Notch1 in mouse vasculature, we observed cardiac and multiple vascular defects in four of the five families. We propose that the limb and scalp defects might also be due to a vasculopathy in NOTCH1-related AOS. Our results suggest that mutations in NOTCH1 are the most common cause of AOS and add to a growing list of human diseases that have a vascular and/or bony component and are caused by alterations in the Notch signaling pathway., (Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based sequencing studies rely on an ad hoc combination of suboptimal analyses. Here we present pedigree-VAAST (pVAAST), a disease-gene identification tool designed for high-throughput sequence data in pedigrees. pVAAST uses a sequence-based model to perform variant and gene-based linkage analysis. Linkage information is then combined with functional prediction and rare variant case-control association information in a unified statistical framework. pVAAST outperformed linkage and rare-variant association tests in simulations and identified disease-causing genes from whole-genome sequence data in three human pedigrees with dominant, recessive and de novo inheritance patterns. The approach is robust to incomplete penetrance and locus heterogeneity and is applicable to a wide variety of genetic traits. pVAAST maintains high power across studies of monogenic, high-penetrance phenotypes in a single pedigree to highly polygenic, common phenotypes involving hundreds of pedigrees.

Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance., Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization., Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.

Computing the genetic relationship between two humans is important to studies in genetics, genomics, genealogy, and forensics. Relationship algorithms may be sensitive to noise, such as that arising from sequencing errors or imperfect reference genomes. We developed an algorithm for estimation of genetic relationship by averaged blocks (GRAB) that is designed for whole-genome sequencing (WGS) data. GRAB segments the genome into blocks, calculates the fraction of blocks sharing identity, and then uses a classification tree to infer 1st- to 5th- degree relationships and unrelated individuals. We evaluated GRAB on simulated and real sequenced families, and compared it with other software. GRAB achieves similar performance, and does not require knowledge of population background or phasing. GRAB can be used in workflows for identifying unreported relationships, validating reported relationships in family-based studies, and detection of sample-tracking errors or duplicate inclusion. The software is available at familygenomics.systemsbiology.net/grab.

The determination of the relationship between a pair of individuals is a fundamental application of genetics. Previously, we and others have demonstrated that identity-by-descent (IBD) information generated from high-density single-nucleotide polymorphism (SNP) data can greatly improve the power and accuracy of genetic relationship detection. Whole-genome sequencing (WGS) marks the final step in increasing genetic marker density by assaying all single-nucleotide variants (SNVs), and thus has the potential to further improve relationship detection by enabling more accurate detection of IBD segments and more precise resolution of IBD segment boundaries. However, WGS introduces new complexities that must be addressed in order to achieve these improvements in relationship detection. To evaluate these complexities, we estimated genetic relationships from WGS data for 1490 known pairwise relationships among 258 individuals in 30 families along with 46 population samples as controls. We identified several genomic regions with excess pairwise IBD in both the pedigree and control datasets using three established IBD methods: GERMLINE, fastIBD, and ISCA. These spurious IBD segments produced a 10-fold increase in the rate of detected false-positive relationships among controls compared to high-density microarray datasets. To address this issue, we developed a new method to identify and mask genomic regions with excess IBD. This method, implemented in ERSA 2.0, fully resolved the inflated cryptic relationship detection rates while improving relationship estimation accuracy. ERSA 2.0 detected all 1(st) through 6(th) degree relationships, and 55% of 9(th) through 11(th) degree relationships in the 30 families. We estimate that WGS data provides a 5% to 15% increase in relationship detection power relative to high-density microarray data for distant relationships. Our results identify regions of the genome that are highly problematic for IBD mapping and introduce new software to accurately detect 1(st) through 9(th) degree relationships from whole-genome sequence data.

Children with special healthcare needs (CSHCN) require health and related services that exceed those required by most hospitalized children. A small but growing and important subset of the CSHCN group includes medically complex children (MCCs). MCCs typically have comorbidities and disproportionately consume healthcare resources. To enable strategic planning for the needs of MCCs, simple screens to identify potential MCCs rapidly in a hospital setting are needed. We assessed whether the number of medications used and the class of those medications correlated with MCC status. Retrospective analysis of medication data from the inpatients at Seattle Children's Hospital found that the numbers of inpatient and outpatient medications significantly correlated with MCC status. Numerous variables based on counts of medications, use of individual medications, and use of combinations of medications were considered, resulting in a simple model based on three different counts of medications: outpatient and inpatient drug classes and individual inpatient drug names. The combined model was used to rank the patient population for medical complexity. As a result, simple, objective admission screens for predicting the complexity of patients based on the number and type of medications were implemented.

The 331-kbp chlorovirus Paramecium bursaria chlorella virus 1 (PBCV-1) genome was resequenced and annotated to correct errors in the original 15-year-old sequence; 40 codons was considered the minimum protein size of an open reading frame. PBCV-1 has 416 predicted protein-encoding sequences and 11 tRNAs. A proteome analysis was also conducted on highly purified PBCV-1 virions using two mass spectrometry-based protocols. The mass spectrometry-derived data were compared to PBCV-1 and its host Chlorella variabilis NC64A predicted proteomes. Combined, these analyses revealed 148 unique virus-encoded proteins associated with the virion (about 35% of the coding capacity of the virus) and 1 host protein. Some of these proteins appear to be structural/architectural, whereas others have enzymatic, chromatin modification, and signal transduction functions. Most (106) of the proteins have no known function or homologs in the existing gene databases except as orthologs with proteins of other chloroviruses, phycodnaviruses, and nuclear-cytoplasmic large DNA viruses. The genes encoding these proteins are dispersed throughout the virus genome, and most are transcribed late or early-late in the infection cycle, which is consistent with virion morphogenesis.