Centrosome clustering control in osteoclasts through CCR5-mediated signaling.

Osteoclasts uniquely resorb calcified bone matrices. To exert their function, mature osteoclasts maintain the cellular polarity and directional vesicle trafficking to and from the resorbing bone surface. However, the regulatory mechanisms and pathophysiological relevance of these processes remain largely unexplored. Bone histomorphometric analyses in Ccr5-deficient mice showed abnormalities in the morphology and functional phenotype of their osteoclasts, compared to wild type mice. We observed disorganized clustering of nuclei, as well as centrosomes that organize the microtubule network, which was concomitant with impaired cathepsin K secretion in cultured Ccr5-deficient osteoclasts. Intriguingly, forced expression of constitutively active Rho or Rac restored these cytoskeletal phenotypes with recovery of cathepsin K secretion. Furthermore, a gene-disease enrichment analysis identified that PLEKHM1, a responsible gene for osteopetrosis, which regulates lysosomal trafficking in osteoclasts, was regulated by CCR5. These experimental results highlighted that CCR5-mediated signaling served as an intracellular organizer for centrosome clustering in osteoclasts, which was involved in the pathophysiology of bone metabolism.

Association between Neuroligin-1 polymorphism and plasma glutamine levels in individuals with autism spectrum disorder.

BACKGROUND: Unravelling the relationships between candidate genes and autism spectrum disorder (ASD) phenotypes remains an outstanding challenge. Endophenotypes, defined as inheritable, measurable quantitative traits, might provide intermediary links between genetic risk factors and multifaceted ASD phenotypes. In this study, we sought to determine whether plasma metabolite levels could serve as endophenotypes in individuals with ASD and their family members. METHODS: We employed an untargeted, high-resolution metabolomics platform to analyse 14,342 features across 1099 plasma samples. These samples were collected from probands and their family members participating in the Autism Genetic Resource Exchange (AGRE) (N = 658), compared with neurotypical individuals enrolled in the PrecisionLink Health Discovery (PLHD) program at Boston Children's Hospital (N = 441). We conducted a metabolite quantitative trait loci (mQTL) analysis using whole-genome genotyping data from each cohort in AGRE and PLHD, aiming to prioritize significant mQTL and metabolite pairs that were exclusively observed in AGRE. FINDINGS: Within the AGRE group, we identified 54 significant associations between genotypes and metabolite levels (P < 5.27 × 10-11), 44 of which were not observed in the PLHD group. Plasma glutamine levels were found to be associated with variants in the NLGN1 gene, a gene that encodes post-synaptic cell-adhesion molecules in excitatory neurons. This association was not detected in the PLHD group. Notably, a significant negative correlation between plasma glutamine and glutamate levels was observed in the AGRE group, but not in the PLHD group. Furthermore, plasma glutamine levels showed a negative correlation with the severity of restrictive and repetitive behaviours (RRB) in ASD, although no direct association was observed between RRB severity and the NLGN1 genotype. INTERPRETATION: Our findings suggest that plasma glutamine levels could potentially serve as an endophenotype, thus establishing a link between the genetic risk associated with NLGN1 and the severity of RRB in ASD. This identified association could facilitate the development of novel therapeutic targets, assist in selecting specific cohorts for clinical trials, and provide insights into target symptoms for future ASD treatment strategies. FUNDING: This work was supported by the National Institute of Health (grant numbers: R01MH107205, U01TR002623, R24OD024622, OT2OD032720, and R01NS129188) and the PrecisionLink Biobank for Health Discovery at Boston Children's Hospital.

BrainGENIE: The Brain Gene Expression and Network Imputation Engine.

In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood-brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles. The performance of BrainGENIE was compared to PrediXcan, a popular method for imputing gene expression levels from genotypes. BrainGENIE significantly predicted brain tissue-specific expression levels for 2947-11,816 genes (false-discovery rate-adjusted p < 0.05), including many transcripts that cannot be predicted significantly by a transcriptome-imputation method such as PrediXcan. BrainGENIE recapitulated measured diagnosis-related gene-expression changes in the brain for autism, bipolar disorder, and schizophrenia better than direct correlations from blood and predictions from PrediXcan. We developed a convenient software toolset for deploying BrainGENIE, and provide recommendations for how best to implement models. BrainGENIE complements and, in some ways, outperforms existing transcriptome-imputation tools, providing biologically meaningful predictions and opening new research avenues.

ADGR: Admixture-Informed Differential Gene Regulation.

The regulatory elements in proximal and distal regions of genes are involved in the regulation of gene expression. Risk alleles in intronic and intergenic regions may alter gene expression by modifying the binding affinity and stability of diverse DNA-binding proteins implicated in gene expression regulation. By focusing on the local ancestral structure of coding and regulatory regions using the paired whole-genome sequence and tissue-wide transcriptome datasets from the Genotype-Tissue Expression project, we investigated the impact of genetic variants, in aggregate, on tissue-specific gene expression regulation. Local ancestral origins of the coding region, immediate and distant upstream regions, and distal regulatory region were determined using RFMix with the reference panel from the 1000 Genomes Project. For each tissue, inter-individual variation of gene expression levels explained by concordant or discordant local ancestry between coding and regulatory regions was estimated. Compared to European, African descent showed more frequent change in local ancestral structure, with shorter haplotype blocks. The expression level of the Adenosine Deaminase Like (ADAL) gene was significantly associated with admixed ancestral structure in the regulatory region across multiple tissue types. Further validations are required to understand the impact of the local ancestral structure of regulatory regions on gene expression regulation in humans and other species.

Neutrophil extracellular traps formation is associated with postoperative complications in neonates and infants undergoing congenital cardiac surgery.

Pediatric patients with congenital heart diseases (CHD) often undergo surgical repair on cardiopulmonary bypass (CPB). Despite a significant medical and surgical improvement, the mortality of neonates and infants remains high. Damage-associated molecular patterns (DAMPs) are endogenous molecules released from injured/damaged tissues as danger signals. We examined 101 pediatric patients who underwent congenital cardiac surgery on CPB. The mortality rate was 4.0%, and the complication rate was 31.6%. We found that neonates/infants experienced multiple complications most, consistent with the previous knowledge. Neonates and infants in the complication group had received more transfusion intraoperatively than the non-complication arm with lower maximum amplitude (MA) on rewarming CPB thromboelastography (TEG). Despite TEG profiles were comparable at ICU admission between the two groups, the complication arm had higher postoperative chest tube output, requiring more blood transfusion. The complication group showed greater neutrophil extracellular traps (NETs) formation at the end of CPB and postoperatively. Plasma histones and high mobility group box 1 (HMGB1) levels were significantly higher in the complication arm. Both induced NETs in vitro and in vivo . As histones and HMGB1 target Toll-like receptor (TLR)2 and TLR4, their mRNA expression in neutrophils was upregulated in the complication arm. Taken together, NETs play a major role in postoperative complication in pediatric cardiac surgery and would be considered a target for intervention. Key points: Neonates and infants showed highest postoperative complications with more upregulation of inflammatory transcriptomes of neutrophils.Neonates and infants with organ dysfunction had more NETs formation with higher plasma histones and HMGB1 levels.

Comprehensive characterization of putative genetic influences on plasma metabolome in a pediatric cohort.

BACKGROUND: The human exposome is composed of diverse metabolites and small chemical compounds originated from endogenous and exogenous sources, respectively. Genetic and environmental factors influence metabolite levels, while the extent of genetic contributions across metabolic pathways is not yet known. Untargeted profiling of human metabolome using high-resolution mass spectrometry (HRMS) combined with genome-wide genotyping allows comprehensive identification of genetically influenced metabolites. As such previous studies of adults discovered and replicated genotype-metabotype associations. However, these associations have not been characterized in children. RESULTS: We conducted the largest genome by metabolome-wide association study to date of children (N = 441) using 619,688 common genetic variants and 14,342 features measured by HRMS. Narrow-sense heritability (h2) estimates of plasma metabolite concentrations using genomic relatedness matrix restricted maximum likelihood (GREML) method showed a bimodal distribution with high h2 (> 0.8) for 15.9% of features and low h2 (< 0.2) for most of features (62.0%). The features with high h2 were enriched for amino acid and nucleic acid metabolism, while carbohydrate and lipid concentrations showed low h2. For each feature, a metabolite quantitative trait loci (mQTL) analysis was performed to identify genetic variants that were potentially associated with plasma levels. Fifty-four associations among 29 features and 43 genetic variants were identified at a genome-wide significance threshold p < 3.5 × 10-12 (= 5 × 10-8/14,342 features). Previously reported associations such as UGT1A1 and bilirubin; PYROXD2 and methyl lysine; and ACADS and butyrylcarnitine were successfully replicated in our pediatric cohort. We found potential candidates for novel associations including CSMD1 and a monostearyl alcohol triglyceride (m/z 781.7483, retention time (RT) 89.3 s); CALN1 and Tridecanol (m/z 283.2741, RT 27.6). A gene-level enrichment analysis using MAGMA revealed highly interconnected modules for dADP biosynthesis, sterol synthesis, and long-chain fatty acid transport in the gene-feature network. CONCLUSION: Comprehensive profiling of plasma metabolome across age groups combined with genome-wide genotyping revealed a wide range of genetic influence on diverse chemical species and metabolic pathways. The developmental trajectory of a biological system is shaped by gene-environment interaction especially in early life. Therefore, continuous efforts on generating metabolomics data in diverse human tissue types across age groups are required to understand gene-environment interaction toward healthy aging trajectories.

Quantitative trait locus analysis for endophenotypes reveals genetic substrates of core symptom domains and neurocognitive function in autism spectrum disorder.

Autism spectrum disorder (ASD) represents a heterogeneous group of neurodevelopmental disorders and is largely attributable to genetic risk factors. Phenotypic and genetic heterogeneity of ASD have been well-recognized; however, genetic substrates for endophenotypes that constitute phenotypic heterogeneity are not yet known. In the present study, we compiled data from the Autism Genetic Resource Exchange, which contains the demographic and detailed phenotype information of 11,961 individuals. Notably, the whole-genome sequencing data available from MSSNG and iHART for 3833 individuals in this dataset was used to perform an endophenotype-wide association study. Using a linear mixed model, genome-wide association analyses were performed for 29 endophenotype scores and 0.58 million common variants with variant allele frequency ≥ 5%. We discovered significant associations between 9 genetic variants and 6 endophenotype scores comprising neurocognitive development and severity scores for core symptoms of ASD at a significance threshold of p < 5 × 10-7. Of note, the Stereotyped Behaviors and Restricted Interests total score in Autism Diagnostic Observation Schedule Module 3 was significantly associated with multiple variants in the VPS13B gene, a causal gene for Cohen syndrome and a candidate gene for syndromic ASD. Our findings yielded loci with small effect sizes due to the moderate sample size and, thus, require validation in another cohort. Nonetheless, our endophenotype-wide association analysis extends previous candidate gene discovery in the context of genotype and endophenotype association. As a result, these candidate genes may be responsible for specific traits that constitute core symptoms and neurocognitive function of ASD rather than the disorder itself.

Evolution of multiple omics approaches to define pathophysiology of pediatric acute respiratory distress syndrome.

Pediatric acute respiratory distress syndrome (PARDS), though both common and deadly in critically ill children, lacks targeted therapies. The development of effective pharmacotherapies has been limited, in part, by lack of clarity about the pathobiology of pediatric ARDS. Epithelial lung injury, vascular endothelial activation, and systemic immune activation are putative drivers of this complex disease process. Prior studies have used either hypothesis-driven (e.g., candidate genes and proteins, in vitro investigations) or unbiased (e.g., genome-wide association, transcriptomic, metabolomic) approaches to predict clinical outcomes and to define subphenotypes. Advances in multiple omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have permitted more comprehensive investigation of PARDS pathobiology. However, omics studies have been limited in children compared to adults, and analyses across multiple tissue types are lacking. Here, we synthesized existing literature on the molecular mechanism of PARDS, summarized our interrogation of publicly available genomic databases to determine the association of candidate genes with PARDS phenotypes across multiple tissues and cell types, and integrated recent studies that used single-cell RNA sequencing (scRNA-seq). We conclude that novel profiling methods such as scRNA-seq, which permits more comprehensive, unbiased evaluation of pathophysiological mechanisms across tissue and cell types, should be employed to investigate the molecular mechanisms of PRDS toward the goal of identifying targeted therapies.

Inhibition of mevalonate metabolism by statins augments the immunoregulatory phenotype of vascular endothelial cells and inhibits the costimulation of CD4+ T cells.

The statin family of therapeutics is widely used clinically as cholesterol lowering agents, and their effects to target intracellular mevalonate production is a key mechanism of action. In this study, we performed full transcriptomic RNA sequencing and qPCR to evaluate the effects of mevalonate on the immunoregulatory phenotype of endothelial cells (EC). We find that mevalonate-dependent gene regulation includes a reduction in the expression of multiple pro-inflammatory genes including TNFSF4 (OX40-L) and TNFSF18 (GITR-L) and a co-incident induction of immunoregulatory genes including LGALS3 (Galectin-3) and LGALS9 (Galectin-9). In functional assays, pretreatment of EC with simvastatin to inhibit mevalonate metabolism resulted in a dose-dependent reduction in the costimulation of CD45RO+ CD4+ T cell proliferation as well as IL-2, IFNγ and IL-6 production versus vehicle-treated EC. In contrast, pre-treatment of EC with L-mevalonate in combination with simvastatin reversed phenotypic and functional responses. Collectively, these results indicate that relative mevalonate metabolism by EC is critical to sustain EC-dependent mechanisms of immunity. Our findings have broad relevance for the repurposing of statins as therapeutics to augment immunoregulation and/or to inhibit local tissue pro-inflammatory cytokine production following transplantation.

Increased Prevalence of Familial Autoimmune Disease in Children With Opsoclonus-Myoclonus Syndrome.

BACKGROUND AND OBJECTIVES: Opsoclonus-myoclonus syndrome (OMS) is a rare autoimmune disorder associated with neuroblastoma in children, although idiopathic and postinfectious etiologies are present in children and adults. Small cohort studies in homogenous populations have revealed elevated rates of autoimmunity in family members of patients with OMS, although no differentiation between paraneoplastic and nonparaneoplastic forms has been performed. The objective of this study was to investigate the prevalence of autoimmune disease in first-degree relatives of pediatric patients with paraneoplastic and nonparaneoplastic OMS. METHODS: A single-center cohort study of consecutively evaluated children with OMS was performed. Parents of patients were prospectively administered surveys on familial autoimmune disease. Rates of autoimmune disease in first-degree relatives of pediatric patients with OMS were compared using Fisher exact t test and χ2 analysis: (1) between those with and without a paraneoplastic cause and (2) between healthy and disease (pediatric multiple sclerosis [MS]) controls from the United States Pediatric MS Network. RESULTS: Thirty-five patients (18 paraneoplastic, median age at onset 19.0 months; 17 idiopathic, median age at onset 25.0 months) and 68 first-degree relatives (median age 41.9 years) were enrolled. One patient developed systemic lupus erythematosus 7 years after OMS onset. Paraneoplastic OMS was associated with a 50% rate of autoimmune disease in a first-degree relative compared with 29% in idiopathic OMS (p = 0.31). The rate of first-degree relative autoimmune disease per OMS case (14/35, 40%) was higher than healthy controls (86/709, 12%; p < 0.001) and children with pediatric MS (101/495, 20%; p = 0.007). DISCUSSION: In a cohort of pediatric patients with OMS, there were elevated rates of first-degree relative autoimmune disease, with no difference in rates observed between paraneoplastic and idiopathic etiologies, suggesting an autoimmune genetic contribution to the development of OMS in children.

WEScover: selection between clinical whole exome sequencing and gene panel testing.

BACKGROUND: Whole exome sequencing (WES) is widely adopted in clinical and research settings; however, one of the practical concerns is the potential false negatives due to incomplete breadth and depth of coverage for several exons in clinically implicated genes. In some cases, a targeted gene panel testing may be a dependable option to ascertain true negatives for genomic variants in known disease-associated genes. We developed a web-based tool to quickly gauge whether all genes of interest would be reliably covered by WES or whether targeted gene panel testing should be considered instead to minimize false negatives in candidate genes. RESULTS: WEScover is a novel web application that provides an intuitive user interface for discovering breadth and depth of coverage across population-scale WES datasets, searching either by phenotype, by targeted gene panel(s) or by gene(s). Moreover, the application shows metrics from the Genome Aggregation Database to provide gene-centric view on breadth of coverage. CONCLUSIONS: WEScover allows users to efficiently query genes and phenotypes for the coverage of associated exons by WES and recommends use of panel tests for the genes with potential incomplete coverage by WES.

Two macrophages, osteoclasts and microglia: from development to pleiotropy.

Tissue-resident macrophages are highly specialized to their tissue-specific microenvironments, activated by various inflammatory signals and modulated by genetic and environmental factors. Osteoclasts and microglia are distinct tissue-resident cells of the macrophage lineage in bone and brain that are responsible for pathological changes in osteoporosis and Alzheimer's disease (AD), respectively. Osteoporosis is more frequently observed in individuals with AD compared to the prevalence in general population. Diagnosis of AD is often delayed until underlying pathophysiological changes progress and cause irreversible damages in structure and function of brain. As such earlier diagnosis and intervention of individuals at higher risk would be indispensable to modify clinical courses. Pleiotropy is the phenomenon that a genetic variant affects multiple traits and the genetic correlation between two traits could suggest a shared molecular mechanism. In this review, we discuss that the Pyk2-mediated actin polymerization pathway in osteoclasts and microglia in bone and brain, respectively, is the horizontal pleiotropic mediator of shared risk factors for osteoporosis and AD.

Genetic variation analyses indicate conserved SARS-CoV-2-host interaction and varied genetic adaptation in immune response factors in modern human evolution.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a pandemic as of early 2020. Upon infection, SARS-CoV-2 attaches to its receptor, that is, angiotensin-converting enzyme 2 (ACE2), on the surface of host cells and is then internalized into host cells via enzymatic machineries. This subsequently stimulates immune response factors. Since the host immune response and severity of COVID-19 vary among individuals, genetic risk factors for severe COVID-19 cases have been investigated. Our research group recently conducted a survey of genetic variants among SARS-CoV-2-interacting molecules across populations, noting near absence of difference in allele frequency spectrum between populations in these genes. Recent genome-wide association studies have identified genetic risk factors for severe COVID-19 cases in a segment of chromosome 3 that involves six genes encoding three immune-regulatory chemokine receptors and another three molecules. The risk haplotype seemed to be inherited from Neanderthals, suggesting genetic adaptation against pathogens in modern human evolution. Therefore, SARS-CoV-2 uses highly conserved molecules as its virion interaction, whereas its immune response appears to be genetically biased in individuals to some extent. We herein review the molecular process of SARS-CoV-2 infection as well as our further survey of genetic variants of its related immune effectors. We also discuss aspects of modern human evolution.

Plasma metabolomics of autism spectrum disorder and influence of shared components in proband families.

Prevalence of autism spectrum disorder (ASD) has been increasing in the United States in the past decades. The exact mechanisms remain enigmatic, and diagnosis of the disease still relies primarily on assessment of behavior. We first used a case-control design (75 idiopathic cases and 29 controls, enrolled at Boston Children's Hospital from 2007-2012) to identify plasma biomarkers of ASD through a metabolome-wide association study approach. Then we leveraged a family-based design (31 families) to investigate the influence of shared genetic and environmental components on the autism-associated features. Using untargeted high-resolution mass spectrometry metabolomics platforms, we detected 19 184 features. Of these, 191 were associated with ASD (false discovery rate < 0.05). We putatively annotated 30 features that had an odds ratio (OR) between <0.01 and 5.84. An identified endogenous metabolite, O-phosphotyrosine, was associated with an extremely low autism odds (OR 0.17; 95% confidence interval 0.06-0.39). We also found that glutathione metabolism was associated with ASD (P = 0.048). Correlations of the significant features between proband and parents were low (median = 0.09). Of the 30 annotated features, the median correlations within families (proband-parents) were -0.15 and 0.24 for the endogenous and exogenous metabolites, respectively. We hypothesize that, without feature identification, family-based correlation analysis of autism-associated features can be an alternative way to assist the prioritization of potentially diagnostic features. A panel of ASD diagnostic metabolic markers with high specificity could be derived upon further studies.

A two-step gas chromatography-tandem mass spectrometry method for measurement of multiple environmental pollutants in human plasma.

Individuals are exposed to a wide variety of chemicals over their lifetime, yet current understanding of mixture toxicology is still limited. We present a two-step analytical method using a gas chromatograph-triple quadrupole mass spectrometer that requires less than 1 mL of sample. The method is applied to 183 plasma samples from a study population of children with autism spectrum disorder, their parents, and unrelated neurotypical children. We selected 156 environmental chemical compounds and ruled out chemicals with detection rates less than 20% of our study cohort (n = 61), as well as ones not amenable to the selected extraction and analytical methods (n = 34). The targeted method then focused on remaining chemicals (n = 61) plus 8 additional polychlorinated biphenyls (PCBs). Persistent pollutants, such as p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE) and PCB congeners 118 and 180, were detected at high frequencies and several previously unreported chemicals, including 2,4,6-trichlorophenol, isosafrole, and hexachlorobutadiene, were frequently detected in our study cohort. This work highlights the benefits of employing a multi-step analytical method in exposure studies and demonstrates the efficacy of such methods for reporting novel information on previously unstudied pollutant exposures.

GenoPheno: cataloging large-scale phenotypic and next-generation sequencing data within human datasets.

Precision medicine promises to revolutionize treatment, shifting therapeutic approaches from the classical one-size-fits-all to those more tailored to the patient's individual genomic profile, lifestyle and environmental exposures. Yet, to advance precision medicine's main objective-ensuring the optimum diagnosis, treatment and prognosis for each individual-investigators need access to large-scale clinical and genomic data repositories. Despite the vast proliferation of these datasets, locating and obtaining access to many remains a challenge. We sought to provide an overview of available patient-level datasets that contain both genotypic data, obtained by next-generation sequencing, and phenotypic data-and to create a dynamic, online catalog for consultation, contribution and revision by the research community. Datasets included in this review conform to six specific inclusion parameters that are: (i) contain data from more than 500 human subjects; (ii) contain both genotypic and phenotypic data from the same subjects; (iii) include whole genome sequencing or whole exome sequencing data; (iv) include at least 100 recorded phenotypic variables per subject; (v) accessible through a website or collaboration with investigators and (vi) make access information available in English. Using these criteria, we identified 30 datasets, reviewed them and provided results in the release version of a catalog, which is publicly available through a dynamic Web application and on GitHub. Users can review as well as contribute new datasets for inclusion (Web: https://avillachlab.shinyapps.io/genophenocatalog/; GitHub: https://github.com/hms-dbmi/GenoPheno-CatalogShiny).

A survey of genetic variants in SARS-CoV-2 interacting domains of ACE2, TMPRSS2 and TLR3/7/8 across populations.

The COVID-19 pandemic highlighted healthcare disparities in multiple countries. As such morbidity and mortality vary significantly around the globe between populations and ethnic groups. Underlying medical conditions and environmental factors contribute higher incidence in some populations and a genetic predisposition may play a role for severe cases with respiratory failure. Here we investigated whether genetic variation in the key genes for viral entry to host cells-ACE2 and TMPRSS2-and sensing of viral genomic RNAs (i.e., TLR3/7/8) could explain the variation in incidence across diverse ethnic groups. Overall, these genes are under strong selection pressure and have very few nonsynonymous variants in all populations. Genetic determinant for the binding affinity between SARS-CoV-2 and ACE2 does not show significant difference between populations. Non-genetic factors are likely to contribute differential population characteristics affected by COVID-19. Nonetheless, a systematic mutagenesis study on the receptor binding domain of ACE2 is required to understand the difference in host-viral interaction across populations.

Personalized iPSC-Derived Dopamine Progenitor Cells for Parkinson's Disease.

We report the implantation of patient-derived midbrain dopaminergic progenitor cells, differentiated in vitro from autologous induced pluripotent stem cells (iPSCs), in a patient with idiopathic Parkinson's disease. The patient-specific progenitor cells were produced under Good Manufacturing Practice conditions and characterized as having the phenotypic properties of substantia nigra pars compacta neurons; testing in a humanized mouse model (involving peripheral-blood mononuclear cells) indicated an absence of immunogenicity to these cells. The cells were implanted into the putamen (left hemisphere followed by right hemisphere, 6 months apart) of a patient with Parkinson's disease, without the need for immunosuppression. Positron-emission tomography with the use of fluorine-18-L-dihydroxyphenylalanine suggested graft survival. Clinical measures of symptoms of Parkinson's disease after surgery stabilized or improved at 18 to 24 months after implantation. (Funded by the National Institutes of Health and others.).

Human autologous iPSC-derived dopaminergic progenitors restore motor function in Parkinson's disease models.

Parkinson's disease (PD) is a neurodegenerative disorder associated with loss of striatal dopamine, secondary to degeneration of midbrain dopamine (mDA) neurons in the substantia nigra, rendering cell transplantation a promising therapeutic strategy. To establish human induced pluripotent stem cell-based (hiPSC-based) autologous cell therapy, we report a platform of core techniques for the production of mDA progenitors as a safe and effective therapeutic product. First, by combining metabolism-regulating microRNAs with reprogramming factors, we developed a method to more efficiently generate clinical-grade iPSCs, as evidenced by genomic integrity and unbiased pluripotent potential. Second, we established a "spotting"-based in vitro differentiation methodology to generate functional and healthy mDA cells in a scalable manner. Third, we developed a chemical method that safely eliminates undifferentiated cells from the final product. Dopaminergic cells thus express high levels of characteristic mDA markers, produce and secrete dopamine, and exhibit electrophysiological features typical of mDA cells. Transplantation of these cells into rodent models of PD robustly restores motor function and reinnervates host brain, while showing no evidence of tumor formation or redistribution of the implanted cells. We propose that this platform is suitable for the successful implementation of human personalized autologous cell therapy for PD.

The Clinical Genome and Ancestry Report: An interactive web application for prioritizing clinically implicated variants from genome sequencing data with ancestry composition.

Genome sequencing is positioned as a routine clinical work-up for diverse clinical conditions. A commonly used approach to highlight candidate variants with potential clinical implication is to search over locus- and gene-centric knowledge databases. Most web-based applications allow a federated query across diverse databases for a single variant; however, sifting through a large number of genomic variants with combination of filtering criteria is a substantial challenge. Here we describe the Clinical Genome and Ancestry Report (CGAR), an interactive web application developed to follow clinical interpretation workflows by organizing variants into seven categories: (1) reported disease-associated variants, (2) rare- and high-impact variants in putative disease-associated genes, (3) secondary findings that the American College of Medical Genetics and Genomics recommends reporting back to patients, (4) actionable pharmacogenomic variants, (5) focused reports for candidate genes, (6) de novo variant candidates for trio analysis, and (7) germline and somatic variants implicated in cancer risk, diagnosis, treatment and prognosis. For each variant, a comprehensive list of external links to variant-centric and phenotype databases are provided. Furthermore, genotype-derived ancestral composition is used to highlight allele frequencies from a matched population since some disease-associated variants show a wide variation between populations. CGAR is an open-source software and is available at https://tom.tch.harvard.edu/apps/cgar/.