Daily Archives: April 18, 2020

WASHINGTON, April 15, 2020 /PRNewswire/ --Vanda Pharmaceuticals Inc. (Vanda) (Nasdaq: VNDA) today announced the initiation of the CALYPSO program to study the role that human genetic variations play in SARS-CoV-2 ("COVID-19") infection and disease progression. As a part of the CALYPSO program, Vanda will collaborate with University of Washington School of Medicine and its Virology Lab on a pharmacogenetics study in patients with COVID-19. The study will focus on the sequencing of the genome of individual patients, as well as the COVID-19 virus, and the identification of genetic factors that correlate with disease progression and outcomes.

In support of this study, Vanda and UW Medicine plan to collect Whole-Genome Sequencing ("WGS") data from over 1,000 patients with COVID-19 infection, and perform Viral Genome Sequencing, which should enable Vanda and the UW Medicine Virology Lab to explore host susceptibility, associations of WGS with clinical outcomes and severity of disease, as well as host-virus interactions. The study is scheduled to begin enrollment in the coming weeks and will be open to patients in hospitals and clinics around the United States.

"We look forward to the advancement of our program and the opportunity to work with and leverage the expertise of UW Medicine to expand our understanding of the COVID-19 infection mechanism," said Mihael H. Polymeropoulos, M.D., President and Chief Executive Officer of Vanda.

"The study has the potential to provide new insights into virushost interactions that could lead to more effective public health strategies and the design and development of vaccines and therapeutics," said Sandra P. Smieszek, Ph.D., Head of Genetics at Vanda. "With the vast amount of data we expect to collect, the team will aim to discern the factors associated with severity and other critical, clinical characteristics of the infected individuals."

"By leveraging our sequencing expertise and capabilities in collaboration with Vanda, we will be able to provide the necessary insight for potentially life-saving solutions for patients," said Alex Greninger M.D., Ph.D., M.S., M.Phil., Assistant Professor, Laboratory Medicine, Assistant Director, Virology Division at the University of Washington School of Medicine. "We believe this collaboration will help answer critical questions and hopefully outcomes in the fight against COVID-19."

"We are grateful to collaborate with Vanda as we try to find better ways to care for people currently suffering from COVID-19, and as we develop plans for the next phase of the national response," said Keith R. Jerome, M.D., Ph.D., Head of Virology Division at the University of Washington School of Medicine. "The approach of combining host and viral genomics to identify the most promising treatments may serve as a model for future efforts around the world. This unique agreement positions UW Medicine and Vanda for potentially changing the course of the COVID-19 pandemic."

"This is the type of collaboration we need to bring solutions to patients suffering in this time of crisis," said Dr. Greninger. "We look forward to getting this important work underway."

About Vanda Pharmaceuticals Inc.

Vanda is a leading global biopharmaceutical company focused on the development and commercialization of innovative therapies to address high unmet medical needs and improve the lives of patients. For more on Vanda Pharmaceuticals Inc., please visit http://www.vandapharma.com and follow us on Vanda's Twitter and LinkedIn.

About UW Virology

The UW Virology is one of nine divisions comprising the Department of Laboratory Medicine at the University of Washington School of Medicine. The UW Medicine Virology Clinical Laboratories perform diagnostic testing for a full range of human pathogens including respiratory viruses, herpes group viruses, HIV, hepatitis, and enteric viruses, and was one of the earliest providers of COVID-19 testing. The Division provides the highest quality patient care and serves as a model of excellence for clinical laboratories across the nation. Its UW Virology Lab is also recognized as a worldwide leader in virology research. UW Medicine Virology's research programs integrate the latest in computational, laboratory, and clinical research methods to advance the understanding of infectious diseases. Many past and current faculty members in the Virology Division have received prestigious awards recognizing their scientific achievements.

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Vanda Contact:

AJ Jones IIChief Corporate Affairs and Communications OfficerVanda Pharmaceuticals Inc.202-734-3400

pr@vandapharma.com

UW Medicine Contact:

Susan GreggDirector, Media Relations 206-616-6730

sghanson@uw.edu

CAUTIONARY NOTE REGARDING FORWARD LOOKING STATEMENTS

Various statements in this release are "forward-looking statements" under the securities laws. These forward-looking statements include, without limitation, statements regarding the design, enrollment and anticipated findings of the CALYPSO program, the promotion of more effective public health strategies and the design and development of vaccines and therapeutics. Forward-looking statements are based upon current expectations that involve risks, changes in circumstances, assumptions and uncertainties. Important factors that could cause actual results to differ materially from those reflected in Vanda's forward-looking statements include, among others: Vanda's ability to enroll patients for, and successfully conduct, the study described in this press release; the ability of Vanda, either alone or with its partners, to process the data collected and subsequently develop effective vaccines or therapeutics; the ability to obtain FDA approval of any such vaccines or therapeutics; and other factors that are set forth in the "Risk Factors" and "Management's Discussion and Analysis of Financial Condition and Results of Operations" sections of Vanda's annual report on Form 10-K for the fiscal year ended December 31, 2019, which is on file with the SEC and available on the SEC's website at http://www.sec.gov. Additional factors may be set forth in those sections of Vanda's annual report on Form 10-Q for the fiscal quarter ended March 31, 2020, to be filed with the SEC in the second quarter of 2020. In addition to the risks described above and in Vanda's annual report on Form 10-K and quarterly reports on Form 10-Q, other unknown or unpredictable factors also could affect Vanda's results. There can be no assurance that the actual results or developments anticipated by Vanda will be realized or, even if substantially realized, that they will have the expected consequences to, or effects on, Vanda. Therefore, no assurance can be given that the outcomes stated in such forward-looking statements and estimates will be achieved. All written and verbal forward-looking statements attributable to Vanda or any person acting on its behalf are expressly qualified in their entirety by the cautionary statements contained or referred to herein. Vanda cautions investors not to rely too heavily on the forward-looking statements Vanda makes or that are made on its behalf. The information in this release is provided only as of the date of this release, and Vanda undertakes no obligation, and specifically declines any obligation, to update or revise publicly any forward-looking statements, whether as a result of new information, future events or otherwise.

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Vanda Pharmaceuticals Announces Initiation of "CALYPSO" to Study the Role of Genetic Variation in COVID-19 Infections in Collaboration With...

INTRODUCTION

Interplanetary space is populated by densely ionizing particle radiation not naturally present on Earth (1). Life on Earth has evolved under the protection of a geomagnetic field, which deflects high-charge, high-energy (HZE) ions; however, the constant flux of HZE ions in deep space is essentially impossible to shield, making astronaut exposures inevitable (2).

In the absence of human epidemiological data for exposures to HZE radiation, uncertainties surround the cancer risk estimates for space flight crews that venture beyond low Earth orbit. The current NASA space radiation cancer risk model is built largely upon epidemiological data from the survivors of the Hiroshima and Nagasaki atomic bombings, a cohort of individuals exposed predominantly to -rays (35), a form of photon radiation. One key assumption in this NASA model is that the spectra of tumor types, and their biologic behaviors, will be similar for individuals exposed to ionizing radiation, whether particle or photon. However, notable physical differences exist between ionizing photon and particle radiation, and these physical differences translate to unique ionization and damage patterns at the molecular, cellular, and tissue levels. HZE ion exposures produce spatially clustered DNA double-strand breaks, along with other DNA lesions in close proximity to break sites (6). In contrast, -rays produce sparse ionization events that are random in spatial distribution and less likely to have additional DNA lesions immediately adjacent to the break sites. Other assumptions in the model are that radiogenic tumors are no more lethal than their sporadic counterparts and that females are at greater risk for radiogenic cancers than males (7).

In assessing cancer risks to astronauts, the premise that HZE ion exposures increase the risk for the same types of tumors that arise in human populations exposed to -rays is supported by the few animal studies of HZE ion carcinogenesis conducted to date (8). These studies, conducted on genetically homogeneous animals, have demonstrated that tumor types arising in HZE ionirradiated animals are the same as those that occur spontaneously in these animals or following exposure to photon radiation (8). However, all previous data are from either inbred mice (9, 10) or rats (11), F1 hybrid mice (12, 13), or rat stocks with limited genetic heterogeneity (11, 1416), and the tumor types that arise in inbred rodents are determined, in very large part, by their genetic background. Therefore, the spectrum of tumors that might arise in a genetically diverse population exposed to HZE ions is unknown.

With the emergence of multiparent outbreeding strategies that produce highly recombinant mouse populations with allelic variants from multiple founder strains (1719), it is possible to model the effects of population diversity in carcinogenesis studies by minimizing the overwhelming effects of genetic background and increasing the phenotypic repertoire available within a test population. These populations also allow for high-precision genetic mapping (18, 20). Quantitative trait locus (QTL) mapping is a powerful forward-genetics approach that allows for unbiased testing of genetic variants that may influence gene-environment interactions for radiation effects (21, 22). Highly recombinant populations were constructed for the purpose of mapping complex traits, and QTL can often be resolved to megabase resolution (1820). In addition, complete sequence information can be used on genotyped individuals by imputing the substantial genomic resources available for the founder strains.

Studying tumors that arise in irradiated, genetically diverse mouse populations presents a unique opportunity to test key assumptions of the NASA risk model, particularly whether HZE ions induce the same tumors by the same mechanisms as -rays. If so, the current practice of extrapolating human epidemiological data from individuals exposed to -rays to astronauts exposed to HZE ions would be a valid approach for risk calculation in the space radiation environment.

To study the effects of HZE ion irradiation in a genetically heterogeneous population, 1850 HS/Npt stock mice (23) of both sexes were genotyped for 77,808 single-nucleotide polymorphism (SNPs) and exposed to (i) 0.4 gray (Gy) of 28Si ions (240 MeV/n) [linear energy transfer (LET), 80 keV/m; = 0.031 particles/m2] or (ii) 56Fe ions (600 MeV/n) (LET, 181 keV/m; = 0.014 particles/m2), (iii) 3 Gy of 137Cs -rays, or (iv) sham irradiation. We chose 56Fe ions because of their high abundance in galactic cosmic radiation (GCR) and because their high charge (Z = +26) makes them particularly damaging (24). The 28Si ions were selected because their LET more closely approximates the dose average LET of secondary fragments generated by GCR penetrating an aluminum spacecraft hull (25). The mice were monitored daily until they reached 800 days of age or became moribund. Comprehensive necropsies were performed on each mouse and involved all organ systems. Each detected lesion was characterized histologically by a board-certified veterinary pathologist. Tumors were the predominant cause of morbidity and mortality for both HZE ionirradiated (n = 622) and -rayirradiated (n = 615) populations as well as for the population of unirradiated mice (n = 613). Overall life span was significantly reduced for irradiated populations (Fig. 1A), which can be attributed to the increased incidence and decreased median survival for radiation-induced tumors. For irradiated mice, populations exposed to 0.4-Gy HZE ions had increased survival times compared to mice exposed to 3.0 Gy of -rays (Fig. 1A). Although these doses seem disparate, their selection is based on preliminary dose-response studies (26), which reveal that 0.4 Gy of HZE ions and 3.0-Gy -rays are each maximally tumorigenic.

Overall survival for HS/Npt mice, plotted as Kaplan-Meier survival, is presented for each exposure group (A). The incidence of specific tumor histotypes (B) and median survival times for these tumors (C) are plotted for each exposure group, which demonstrates that certain tumor types occur at an increased frequency following exposures to radiation of specific qualities and survival times in irradiated mice are decreased for some tumor types. The incidence of specific tumor histotypes within HS/Npt families is plotted for unirradiated (D), -rayirradiated (E), and HZE ionirradiated families (F) and demonstrates that specific tumor types often occur at very high incidence within some families and not at all in others, indicating heritability of tumor susceptibility. Furthermore, adjacent families are more closely related, and tumor incidences, for example, family 23 and adjacent families, have a high incidence of B cell lymphoma. The 47 HS/Npt families are arranged along the x axis (D to F).

A wide variety of tumor diagnoses [82 distinct tumor histotypes (table S1)] were observed in HS/Npt mice. Although most of these tumor types were rare, 18 histotypes were observed at incidences greater than 1%. Overall, the spectra of tumor histotypes produced in genetically diverse populations exposed to HZE ions and -rays were similar (Fig. 1B). Furthermore, tumor types induced by radiation were generally similar to those arising spontaneously in HS/Npt mice; however, radiation-exposed populations demonstrated decreased median survival times associated with tumor development (Fig. 1C and figs. S7 to S22) and increased incidences for specific tumor types, such as leukemias and Harderian gland adenocarcinomas, following radiation (Fig. 1B). The structure of the HS/Npt population can be divided into families that consist of mice more closely related to one another. Many tumor histotypes show high incidences within some families but are absent or rare in others (Fig. 1, D to F), which is consistent with genetic susceptibility to certain tumor types. Furthermore, certain tumorsparticularly lymphomas, pulmonary adenocarcinomas, hepatocellular carcinomas, Harderian gland tumors, and myeloid leukemiasdemonstrate a periodicity in tumor incidence (Fig. 1, D to F) where adjacent families often display similar incidences, which could be predicted on the basis of the circular breeding design used to generate HS/Npt, in which adjacent families are more related to one another than families further removed.

Although the tumor spectra are similar for each irradiated population, the different radiation qualities demonstrate varied efficiencies for producing specific tumor histotypes. -rayirradiated mice were at greater risk for myeloid leukemia, T cell lymphoma, pituitary tumors, and ovarian granulosa cell tumors than unirradiated mice; HZE ionirradiated mice demonstrated an intermediate susceptibility to these histotypes (Fig. 1B). For Harderian gland tumors, thyroid tumors, hepatocellular carcinomas, and sarcomas, HZE ion and -rayirradiated mice were at a similarly and significantly increased risk compared to unirradiated controls (fig. S7 to S22).

NASA permissible exposure limits for radiation limit the number of days an astronaut can spend in space based on modeled cancer risk. These limits are different for men and women (27) due primarily to epidemiological data that indicate that women are at greater risk for radiogenic cancers than men due to their longer life spans and susceptibility to specific cancer types, such as lung, ovarian, and breast carcinomas. Female HS/Npt mice have longer life spans than males (P = 2.7 106, log-rank test), with unirradiated females living 43 days longer (686.1 days), on average, than males (643.2 days) (fig. S1A). In contrast, no survival difference is observed between -rayirradiated females and males (P = 0.51) or HZE ionirradiated females and males (P = 0.06), indicating that female HS/Npt mice are more susceptible to radiation-induced morbidities and mortalities than males (fig. S1, B and C). Irradiated female mice had increased incidences of (i) ovarian tumors, (ii) mammary tumors, (iii) central nervous system tumors (pituitary adenomas, choroid plexus tumors, and ependymomas), (iv) diffuse large B cell and lymphoblastic B cell lymphomas, (v) osteosarcomas, and (vi) leiomyosarcomas (fig. S1D). Female mice were at lower risk for radiogenic lung cancer (fig. S1D and table S1), which is a major contributor to limiting flight time for female astronauts. Modeling risk by sex in humans has been confounded by different smoking rates between men and women in the atomic bomb survivor cohort (28).

To determine whether the genetic variants that increase tumor susceptibility following -ray irradiation also increase tumor susceptibility following HZE ion irradiation, genome-wide association mapping was performed for 18 tumor types in which there was an incidence of greater than 1%. Genomes were reconstructed for each mouse using a probabilistic model to predict founder haplotypes from high-density genotype data (18). Reconstructed genomes represent the unique accumulation of meiotic events for each individual and form a scaffold for the imputation of known sequencing information from the eight parental inbred strains. Polygenic covariance among related individuals is of significant concern in multiparent crosses and was corrected for during QTL mapping with a kinship term (18, 29). Mapping was performed for each phenotype using both a generalized linear mixed-effects model and proportional hazards regression model with the aforementioned kinship to adjust for polygenic covariance between related mice. To determine the significance thresholds for a model in which no QTL is present, the phenotypes were permuted, the regression model was run, and the maximum statistic was retained from each permutation (30). The 95% significance threshold was minimally variable between phenotypes with a mean threshold of log(P) > 5.8, and this value was used to identify significant associations. This is consistent with the estimated 0.05 Bonferroni genome-wide corrected threshold of log(P) > 6.0, which is considered overly conservative for QTL mapping (30).

At least one QTL was identified for 13 of the 18 tumor phenotypes examined. For tumor incidence, 35 QTL were identified with an average confidence interval of 3.4 Mb (table S2). For QTL at the 95% confidence threshold, effect sizes average 3.7% of the phenotypic variance with a range of 0.75 to 7.46%. For most of the tumors, the genetic architecture was complex with multiple QTL individually explaining a small proportion of the total variance. Although loci with moderate effects on the phenotype were most common, 11 large effect QTL were observed for seven tumor histotypes, with effect sizes greater than 5% (table S2).

To determine potential effects of genetic variants on tumor latency following irradiation, mapping was also performed using proportional hazards regression model (table S3) and 38 QTL were identified for 12 tumor types. QTL associated with tumor survival times mirrored those identified for tumor incidence, indicating that the genetic variants that control susceptibility to radiation-induced tumors also determine latencies.

Neoplasia is a binomially distributed trait, and therefore, the power to detect significant associations is primarily dependent on tumor incidence and QTL effect size. This leads to important considerations for the ultimate goal of this analysis, which is to determine similarities between QTL for specific neoplasms in populations exposed to different qualities of radiation. For some tumor types, a significant peak was observed in one exposure group with a suggestive peak present at the same locus in the alternative exposure group. We speculate that the reason certain radiation qualities produce only suggestive QTL for certain tumor phenotypes is likely due to decreased mapping power as a result of the variation in incidence between groups. In these cases, if the peak was more significant when combining radiation groups, the QTL was considered significant for all irradiated animals regardless of radiation quality.

Thyroid tumors are a well-known radiation-induced entity for both humans and mice; however, relatively little is known about genetic variants that increase susceptibility to this disease in mice. In HS/Npt mice, spontaneous thyroid adenomas occurred at relatively low frequencies and had a uniformly late onset, with tumors occurring between 700 and 800 days of age (Fig. 2A). In contrast, thyroid tumors arising in HZE ion or -rayexposed mice occur with significantly earlier onsets, with tumors arising as early as 250 days of age (Fig. 2A).

Thyroid follicular adenoma Kaplan-Meier survival estimate (A) along with genome-wide association plots for thyroid adenoma in HZE ionirradiated, -rayirradiated, HZE ion and -rayirradiated, and unirradiated mice (B) and an expanded plot for chromosome 2 (C), which contains the most significant association locus; gray lines indicate 95% (upper line) and 90% confidence (lower line) for log10(P values). Genome-wide association results reveal significant results in HZE ion and -rayirradiated mice that are further bolstered by combining the groups. The top panel of (D) shows strains that contribute the reference allele for the SNPs highlighted in red in the middle panel, indicated by vertical lines (D); the C57BL/6J strain contributes an allele that differs significantly from the other seven strains. The middle panel shows the log10(P value) of each SNP in the interval (D); the most significant SNPs are highlighted in red, and the bottom panel lists genes within the QTL interval. Genes that contain splice site, missense, or stop-related SNPs are colored red (D). Resample model averaging was performed within chromosome 2 to compare the distribution of peak log10(P values) for each exposure group (E); there is broad overlap for HZE- and -rayirradiated mice, and grouping all irradiated mice together further narrows the distribution of peak log10(P values). Mbp, megabase pair.

Association mapping reveals a significant 3.4-Mb interval on chromosome 2 for HZE ionexposed animals (Fig. 2, B and C). The same locus is identified in the -rayirradiated population if the significance threshold is decreased to a level at which 30% of identified QTL will be false positives. Combining both irradiated populations markedly increases the significance of the QTL identified on chromosome 2. The QTL interval (119 to 125 Mb) contains 39,179 SNPs (Sanger Mouse Genomes, REL-1505) and 142 genes (Ensembl version 85) (Fig. 2D). Within the QTL region, the C57BL/6J parental strain contains an introgression from the Mus musculus musculus genome (31); we found that HS/Npt mice carrying the C57BL/6J haplotype at the QTL have increased thyroid tumor incidence regardless of whether they are exposed to HZE ions or -rays.

To further explore the possibility that the QTL identified on chromosome 2 controls susceptibility following -ray and HZE ion exposures, we used a nonparametric resample model averaging procedure (32) across the entire chromosome to identify genomic loci that consistently reappear in resampled populations. Briefly, genome scans are repeated for each new dataset created, in which some individuals may be sampled more than once and some not at all (32). Resample model averaging consistently identifies the same locus for all groups of mice, regardless of radiation exposure (Fig. 2E). Furthermore, the resample model averaging procedure identifies the same locus for tumors arising spontaneously (Fig. 2E). Data from this tumor phenotype indicate that the same inheritable genetic variants contribute to an individuals risk of developing thyroid cancer, regardless of radiation exposure.

Acute myeloid leukemia (AML) is another common radiation-induced tumor in both mice and humans (33, 34). In concordance with previous studies conducted with inbred mice (26), -ray exposures in HS/Npt mice are more efficient at inducing AML than HZE ion exposures. In our -irradiated mice, 15.6% (96 of 615) developed AML compared to 2.9% (18 of 622) of those exposed to HZE ions and 1.6% (10 of 613) of unirradiated mice. AML median survival times were similar for all groups (Fig. 3A). Association mapping revealed a significant QTL for the -irradiated population on chromosome 2 that reached the 95% confidence threshold (Fig. 3, B and C), but no QTL was observed for the HZE ionexposed population, in which the incidence of AML was much lower. However, when grouping HZE ion and -rayirradiated mice together, the same QTL was significantly bolstered (Fig. 3B). If the susceptibility alleles identified at this locus were only contributing to disease following -ray irradiation and were, therefore, randomly distributed among the affected mice in the HZE ionexposed group, then we would expect the log10(P values) to decrease when combining -irradiated mice; however, the log10(P value) for this locus significantly increases when repeating the mapping procedure included all irradiated mice.

(A) Kaplan-Meier plots for myeloid leukemia demonstrate similar median survival estimates for myeloid leukemia between groups. (B) Genome-wide association procedures identify a narrow QTL on chromosome 2; two gray lines indicate 95% (upper line) and 90% confidence (lower line) for log10(P values). Expanded mapping results are depicted in (C) along with contributing strains for the reference allele. The A/J, AKR/J, C57BL/6J, DBA/2J, and LP/J strains contribute alleles that differ from the other strains, indicated by vertical lines in the top panel (C). The middle panel shows the log10(P value) of each SNP in the interval. The most significant SNPs are highlighted in red. The bottom panel shows the genes in the QTL interval. Genes that contain splice site, missense, or stop-related SNPs are indicated in red. Copy number results for Spi1 and Asxl1 in splenic samples from mice diagnosed with myeloid leukemia are plotted by exposure group (D).

Radiation-induced AML is a well-characterized disease in mice (10, 35, 36) and is most commonly the result of a radiation-induced minimally deleted region on chromosome 2 containing the PU.1 gene (current murine nomenclature, Spi1) and a recurrent point mutation that inactivates the remaining Spi1 allele (37). Figure 3C depicts mouse chromosome 2 with the positions of the QTL identified in our irradiated mice and the Spi1 gene. To test the hypothesis that AMLs occurring in HZE ionexposed animals will contain the same molecular aberrations know to occur in AML arising in -rayexposed mice, the copy number for Spi1 was investigated in leukemia samples to assess for deletions. As expected, most of the leukemias occurring in -rayexposed mice had a deletion in one copy of Spi1. In contrast, Spi1 deletions in spontaneously occurring AML were less common (Fig. 3D). Similar to -rayirradiated mice, leukemias that developed in mice exposed to HZE ions, although fewer in number, also have an increased incidence of Spi1 deletion. This finding indicates that AML arises by similar molecular mechanisms following exposures to HZE ions or -rays.

Because the QTL identified on chromosome 2 is approximately 60 Mb from the commonly deleted region containing Spi1 and because radiation-induced deletions can be notoriously large, we considered the possibility that the identified QTL was also deleted in these leukemias, resulting in loss of one copy of the QTL region. To test this hypothesis, we determined the copy number for a gene located at distal to the QTL support interval, Asxl1. As expected, we found that Asxl1 was not deleted in any sample in which Spi1 was not deleted; however, in 69% of cases with a Spi1 deletion, Asxl1and presumably the entire QTL regionwas also deleted (Fig. 3D). This demonstrates that most of the radiation-induced AML cases arose from progenitor cells haploinsufficient for the entire QTL region.

HZE ion and, to a lesser extent, -ray irradiation were particularly effective in inducing Harderian gland tumors at the doses used in this study, which was expected on the basis of extensive published radiation quality data on these tumors (8, 38). In the HZE ionirradiated group, Harderian gland tumors were observed in 22.7% (221 of 622) of mice and 3.2% (20 of 622) were malignant. In the -irradiated group, 15.3% (94 of 615) of mice developed Harderian gland tumors and 2.7% (17 of 615) were malignant. In contrast, spontaneous Harderian gland tumors occurred in only 4.1% (25 of 613) of unirradiated mice and 0.7% (4 of 613) were malignant. Despite the differences in tumor incidences following irradiation, median survival times for Harderian gland adenocarcinoma were similar for all groups (HZE ion, 582 days; -ray, 571 days; and unirradiated mice, 571 days).

Two QTL were observed for Harderian gland adenocarcinomas in HZE ionirradiated mice, one on chromosome 4 and another on chromosome 9 (Fig. 4A). The 1.7-Mb interval identified on chromosome 4 (Fig. 4B) is similar to previously discussed QTL regions in that combining both irradiated populations markedly increases the significance of this locus, which suggests that this QTL is associated with Harderian gland adenocarcinoma susceptibility in both HZE ion and -rayirradiated mice. In contrast, a 2.3-Mb QTL interval on chromosome 9 is observed only in HZE ionirradiated mice, and the locus is absent when combining all irradiated mice and repeating the mapping procedure (Fig. 4C). To further evaluate these QTL, resample model averaging was performed within chromosomes 4 and 9 to determine the distribution of peak log10(P values) along each chromosome. For chromosome 4, there is substantial spatial overlap identified in peak log10(P value) associations in the HZE ionexposed population and the -rayirradiated population, and the HZE ion and -rayirradiated population yields the most consistent identification of the QTL region (Fig. 4D). In contrast, although nearly all identified peak log10(P values) were identified in the 2.3-Mb QTL interval on chromosome 9 for HZE ionirradiated mice, the distributions of peak log10(P values) for other exposure groups do not substantially overlap and are widely distributed along the chromosome (Fig. 4E). The resample model averaging results indicate that while the chromosome 4 QTL contributes to susceptibility to Harderian gland adenocarcinomas in both HZE ion and -rayirradiated populations, the QTL identified on chromosome 9 appears to only be involved in Harderian adenocarcinoma susceptibility following HZE ion exposures.

Genome-wide association plots for Harderian gland adenocarcinoma (A) for HZE ionirradiated, -rayirradiated, HZE ion and -rayirradiated, and unirradiated mice; two gray lines indicate 95% (upper line) and 90% confidence (lower line) for log10(P values). Chromosome 4, which is expanded in (B), reveals a significant QTL associated with HZE ion irradiation, which is further increased significantly when grouping all irradiated mice (HZE ion and -ray irradiated) together, which indicated that the genetic variants in this location are important for Harderian gland adenocarcinoma following exposures to either HZE ion or -ray irradiation. In contrast, chromosome 9, which is expanded in (C), reveals a significant QTL associated only with HZE ion irradiation; this locus is absent when grouping all irradiated mice (HZE ion and -ray irradiated) together, which suggests that the allele(s) present in this region may only play a role for HZE ioninduced tumors. Resample model averaging was performed within chromosomes containing significant QTL. There is significant spatial overlap identified on chromosome 4 for peak log10(P value) associations in the HZE ionexposed population, the -rayirradiated population, and the HZE ion and -rayirradiated population that demonstrates the most consistent identification of the QTL region (D). In contrast, although nearly all identified peak log10(P values) were identified in the chromosome 9 QTL interval for HZE ion irradiated mice, the peak log10(P values) for other exposure groups are widely distributed along the chromosome (E).

In addition to looking for similarities between individual, selected QTL for HZE ion and -rayexposed populations, we also sought a more holistic method in which entire genome-wide association results could be compared between groups in an unsupervised process. We used hierarchical clustering to create cluster dendrograms using entire genome-wide scans for a given phenotype. By considering results from genome-wide associations, rather than individualized peaks observed within genome-wide associations, we submit for comparison not only highly significant QTL regions but also the numerous loci detected with lower confidence.

Unsupervised hierarchical clustering of genome scans creates significant clustering events that often occur for the same histotype regardless of radiation exposure (Fig. 5A). Multiple tumor histotypesincluding mammary adenocarcinoma, thyroid adenoma, and hepatocellular carcinomacluster by histotype, regardless of radiation exposure. To demonstrate and validate the methodology of QTL clustering, genome-wide scans for coat colors in each treatment group are evaluated and coat color genome-wide scans cluster together, as expected (Fig. 5B). These results further support the hypothesis that host genetic factors are highly important in determining risk of radiation carcinogenesis, whether following HZE ion or -ray exposures.

(A) Unsupervised hierarchical clustering of genome-wide association scans for tumor phenotypes reveals that the most significant clustering events often occur for the same histotype regardless of radiation exposure; these include mammary adenocarcinoma, thyroid adenoma, and hepatocellular carcinoma. (B) As expected, clustering genome scans for coat color demonstrates the expected results: that genome scans cluster together despite exposure group. The green line represents the 99% confidence level of the most significant dendrogram heights by permutations (log10 values permuted with genetic markers) to determine a distribution of dendrogram heights under the null hypothesis that no associations exist (C), demonstrating that the observed clusters are highly unlikely to occur randomly.

Permissible exposure limits for astronauts are based on the risk of death from cancer rather than cancer development, and the incidence to mortality conversion used in the risk calculation uses spontaneously occurring cancers in the U.S. population. Thus, there is an assumption that radiogenic tumors are no more lethal than spontaneous tumors. To determine whether tumors that arise following HZE ion exposure are more malignant than their counterparts arising in unirradiated or -rayirradiated mice, metastatic disease was characterized for each group. Pulmonary metastases were consistently observed in cases of hepatocellular carcinoma, Harderian gland adenocarcinoma, osteosarcoma, and ovarian granulosa cell tumor. Metastases were no more frequent in irradiated animals than in controls, and there was no significant difference in metastatic incidence between HZE ionirradiated mice and -rayirradiated mice (fig. S5A), and pulmonary metastatic density is similar between groups (fig. S5, B to D).

Tumor latency following irradiation was compared between exposure groups using survival statistics. Differences in tumor latency in this context indicate a decrease in time for tumor initiation or promotion. Since radiation is efficient at both initiation and promotion, decreased latencies are expected for irradiated population. Tumor progression is not evaluated, and our results therefore do not demonstrate whether tumors arising in irradiated individuals are more likely to progress rapidly than those arising spontaneously. As expected, tumors arising in both HZE ion and -rayirradiated mice show significantly decreased latencies in comparison to the unirradiated population (fig. S7 to S22). However, HZE ions did not further decrease latencies when compared to -rayirradiated mice.

Carcinogenesis as a result of space radiation exposure is considered the primary impediment to human space exploration (2). Compared to forms of radiation found naturally on Earth, including x-rays, -rays, and particles, HZE ions in space are much more difficult to shield (2) and have a distinct ionization pattern that aligns along dense track structures, resulting in clustered damage to chromatin (6). Because HZE ions, a highly penetrating component of GCRs, are not amenable to shielding (28, 29), exposure risks are inherent to manned missions in interplanetary space, but estimating the risk associated with this unique form of particle radiation is complicated by the essential lack of data for human exposures (28). As a substitute, human exposure data from other forms of ionizing radiation, primarily -ray (35) photon radiation, are used in cancer risk models with the assumption that photon and particle radiation have qualitatively comparable biological effects.

Animal models are a vital component in determining the validity of the extrapolation of human terrestrial radiation exposure data to exposures that will occur in astronauts in the space radiation environment. To date, carcinogenesis studies designed to evaluate the effects of HZE ions have used rodents with limited genetic heterogeneity (916). The advantage of removing genetic variability in animal models is the consequent decrease in phenotypic variability, which allows for fewer individuals to detect potential environmental effects on phenotype; the disadvantage is that strain-specific responses in genetically identical populations are significant and can obscure the variability that one might expect in a diverse population, such as humans. By using a genetically diverse population with a wide range of tumor susceptibilities, the spectra of tumors that occur following exposures to particle and photon radiation can be compared. The results of this study indicate that the spectrum of tumor histotypes observed in a genetically diverse population exposed to particle radiation is not unique to that observed in a population exposed to photon radiation or to the tumor spectrum observed in an unirradiated population. Despite the similarities observed in tumor spectra following radiation exposures, the radiation qualities and doses used for this study have unique efficiencies at producing specific tumor types, and while this work demonstrates that the underlying genetics of susceptibility can be similar for tumorigenesis following both high- and low-LET radiation, further work is necessary to define risks for specific tumor histotypes based on exposures.

This study uses a highly recombinant mouse population (HS/Npt stock) that is genetically diverse and designed for genome mapping (1921, 23), a forward-genetics approach that allows for an unbiased search of the entire genome for genetic associations. In contrast, genetically engineered mouse models rely on a reverse-genetics approach in which a given gene is first altered and the resulting phenotypes are then characterized. Studies using forward-genetics are most informative in populations that contain abundant genetic and phenotypic diversity. HS/Npt mice are a multiparent cross derived from eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J, and LP/J); each individual contains a unique mosaic of founder haplotypes and a high degree of heterozygosity, and recombination events become increasingly dense with each generation. Our population of HS/Npt mice was obtained from generation 71 of circular outbreeding. Creating these populations is not trivial and has been a central goal of communities involved in genetics research over the past few decades, resulting in the creation of rodent populations ideal for genome mapping (1820, 3942).

Genome mapping allows the discovery of QTL associated with susceptibility to complex traits, such as radiogenic cancers; this approach is uniquely suited to comparing inheritable risk factors for cancers following exposures to unique carcinogens, such as particle and photon radiation. In broader terms, this work demonstrates the utility of highly recombinant mouse models created for genetic mapping in carcinogenesis studies, an application that has not been previously attempted. Mapping QTL in carcinogenesis studies provides inherent challenges due to the structure of binomial data, potential confounding causes of death following irradiation and aging, the fundamental stochastic nature of radiation tumorigenesis, and incomplete penetrance of potential allelic variants. Despite these challenges, we were able to map QTL for 13 neoplastic subtypes and many of these identified loci are previously unidentified.

At the doses used in this study, HZE ions appear to be less effective than -rays in inducing precursor T cell lymphoblastic lymphoma (pre-T LL) and ovarian tubulostromal adenomas and granulosa cell tumors. This may be due to a combination of dose inhomogeneity in HZE ionirradiated tissues and the major role cell killing plays in the etiology of these specific tumors. pre-T LL can be prevented by transplanting irradiated mice with unirradiated syngeneic bone marrow cells or by shielding some of their bone marrow during irradiation (43, 44). The underlying mechanism by which unirradiated bone marrow cells suppress lymphomagenesis may involve a cell competition process by which older T cell progenitors resident in the thymus are normally replaced by fresh progenitors that immigrate from the bone marrow. Radiation kills these fresh bone marrow cells or reduces their fitness, which, in turn, prolongs the time that older T cell progenitors already in the thymus survive and self-renew. This, along with the increased proliferative cycles of the older T cell progenitors needed to maintain production of mature T cells, results in a corresponding increase in the oncogenic mutations that they accumulate and a concomitant increase in lymphomagenesis (45). Replenishing dead or damaged bone marrow cells by transplantation or preventing their damage through shielding suppresses lymphomagenesis.

At the 3-Gy dose of -rays used in this study, all of the bone marrow cells are uniformly irradiated. This is not the case for HZE particle radiation. The average diameter of a murine bone marrow cell nucleus is around 6 m (46). At the fluence of HZE ions used in this study, the probability that a 6-m-diameter nucleus will be traversed by a 28Si ion and a 56Fe particle is 0.88 and 0.40, respectively. On the basis of a Poisson distribution, the probabilities of a nucleus not being traversed at all are 0.41 and 0.67 for 28Si and 56Fe irradiation, respectively. Thus, many of the T cell progenitors in the bone marrow are not irradiated (although they receive a small dose from -rays). These cells should exert a protective effect similar to transplanting unirradiated bone marrow cells or shielding some of the bone marrow during irradiation, rendering HZE ions less efficient for lymphomagenesis. Given that most of the pre-T LL in the HZE ionirradiated group are likely spontaneous, it is expected that they cluster more closely to spontaneous pre-T LL than to -rayinduced pre-T LL.

The mechanism leading to murine tumors of ovarian surface epithelium origin is well understood. Loss of primordial follicle oocytes by radiation-induced apoptosis results in a decrease in estrogen production, which, in turn, leads to elevated levels of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) in the circulation. FSH and LH drive proliferation of ovarian surface epithelium cells (47). Ovarian tumors can be induced in some animal models by artificially manipulating levels of these hormones (4749). Irradiated mice can be protected from tubulostromal adenomas and granulosa cell tumors by shielding one ovary during irradiation or by transplanting the mice with an unirradiated ovary (50, 51); these interventions protect some oocytes and thereby maintain proper regulation of FSH and LH levels.

Assuming that the target cells are primordial follicle oocytes with a diameter of 12 m, the probabilities of no traversals are 0.2 for 56Fe and 0.03 for 28Si at the 0.4-Gy dose used here. The probabilities for one or fewer traversals are 0.52 for 56Fe and 0.14 for 28Si. Whether a sufficient number of follicles survive at 0.4 Gy to account for the observed ovarian tumor sparing is unknown. Mishra and colleagues (52) observed a dose-dependent decrease in primordial stage follicles in C57BL/6 mice 8 weeks after irradiation with 56Fe ions (600 MeV/n). Sixteen percent of the follicles survived at the 0.3-Gy dose, and normal levels of serum FSH and LH were present; at 0.5 Gy, only 1% of the follicles survived and an increase in serum FSH was observed. Caution is needed in using Mishras results in interpreting our own since we used mice with different genetic backgrounds and the FSH and LH levels in the 0.3 Gyirradiated mice may increase relative to unirradiated controls if time points beyond 8 weeks are assayed. In any event, microdosimetric effects should be incorporated into any risk model for tumors in which cell killing plays a prominent role.

The location of the chromosome 2 QTL in a region frequently deleted in radiogenic AMLs may be happenstance, but there are scenarios in which its chromosomal location would be crucial to its function. One possibility is that the polymorphism increases the frequency of AML-associated chromosome 2 deletions in irradiated hematopoietic cells by controlling the spatial confirmation of the chromosome such that the proximal and distal deletion breakpoints are in close proximity to one another (46). This type of proximity mechanism has been evoked to explain recurrent chromosomal rearrangements seen in radiation-induced papillary thyroid carcinoma and some spontaneous cancers (53, 54). In this scenario, the QTL could be a structural polymorphism (e.g., segmental duplication or interstitial telomeric sequence), which would affect chromosomal conformation, yielding a different conformation in susceptible mouse strains than resistant strains. Structural polymorphisms are easily missed in the assembly of the strain-specific genomic sequences used for mapping studies, so we would be unaware of its existence. A second possibility is that the polymorphism is in a gene needed for myeloid progenitor cell survival. Mouse strains resistant to myeloid leukemia would have a hypomorphic allele of this gene. If one copy is lost (i.e., through radiation-induced deletion), then the remaining copy would be insufficient for cell survival. Thus, in mouse strains resistant to radiogenic AML, a chromosome 2 deletion, which is the first step in radiation leukemogenesis, is a lethal event and leukemogenesis is thereby halted. Susceptible strains would have a fully functional allele of the gene, so that if one copy is deleted, the remaining copy maintains cell viability, allowing further leukemogenic events to occur (46). A caveat to both the chromosome conformation and haploinsufficiency scenarios is that the chromosome 2 deletions mapped in radiogenic AMLs from the F1 progeny of AML-susceptible CBA/H mice and AML-resistant C57BL/6 mice do not occur preferentially in the CBA/H origin chromosome (55). However, in that study, only 10 tumors were informative. In addition, susceptibility to radiogenic AML is multigenic, so it is possible that the difference in susceptibility between the CBA/H and C57BL/6 strains is not due to the chromosome 2 QTL.

HZE ions seem particularly effective in inducing Harderian gland tumors at the doses used in this study. This result was expected on the basis of extensive published radiation quality data on these tumors (8, 38). The mechanism responsible for higher tumorigenic efficacy of HZE ions relative to -rays is unknown; however, we have identified a QTL associated with Harderian gland adenocarcinoma following HZE ion exposures that does not appear to lend susceptibility to the same tumor following -ray exposures (Fig. 4C). Furthermore, HZE ioninduced Harderian gland adenomas and adenocarcinomas cluster away from spontaneous and -rayinduced Harderian gland tumors (Fig. 5), indicating non-overlap of some of the susceptibility loci. There are data that suggest that HZE ion irradiation has an effect on tumor promotion that -ray irradiation lacks. The observation is that pituitary isografts, which result in elevated levels of pituitary hormones, enhance the induction of Harderian gland tumors and decrease their latency in mice irradiated with -rays or fission neutrons but do not increase tumor prevalence in mice irradiated with 56Fe ions (600 MeV/n) (12). This would explain the high relative biological effectiveness (RBE) for 56Fe ions. It would also render QTLs that act in the promotion of -ray and spontaneous tumors irrelevant to HZE ioninduced tumors.

The use of unsupervised clustering on genome-wide association results is a novel approach to search for shared tumorigenic mechanisms between radiogenic and spontaneous tumors or between tumors induced by different radiation qualities. Potentially, the results could be used to inform risk modeling. For example, using the 99% confidence interval as a cutoff, thyroid adenomas, pituitary tumors, osteosarcomas, B cell lymphoblastic leukemia, mammary tumors, and hepatocellular carcinomas cluster by histotypes regardless of whether they arose in HZE ionirradiated or -rayirradiated mice. Of these, the incidences of thyroid tumors, pituitary tumors, and osteosarcomas are significantly increased following exposures to either HZE ions or -rays. Taking pituitary adenoma as an example, these findings suggest that it would be reasonable to extrapolate the risk of HZE ioninduced pituitary adenoma as a multiple of -rayinduced pituitary adenoma risk (i.e., using a relative risk model). Because there were too few spontaneous pituitary adenomas to position them on the dendrogram, we cannot determine whether the risk of HZE ioninduced pituitary adenoma could reasonably be modeled on the basis of the incidence of the spontaneous tumor. Another pattern of association is observed for Harderian gland adenoma and follicular B cell lymphoma in which, at the 99% confidence interval, spontaneous tumors cluster with -rayinduced tumors but not with HZE ioninduced tumors. There are a number of ways that this could occur. Three possibilities are as follows: (i) HZE ions act through a tumorigenic mechanism different from that of spontaneous and -rayinduced tumors. (2) HZE ions bypass the need for one or more of the genetically controlled steps required for spontaneous and -rayinduced tumors, and (iii) there are multiple pathways to tumor formation, and HZE ion irradiation forces tumorigenesis through only one (or a subset) of them. Harderian gland tumors may fall into the second possibility. As described earlier, observations on mice receiving pituitary isografts before irradiation suggest that HZE ions may have Harderian gland tumor promotion effects that -rays lack. If so, the QTL controlling those effects would be inconsequential in the tumorigenesis of HZE ioninduced Harderian gland tumors, and those tumors would cluster away from their spontaneous and -rayinduced counterparts. Whether a relative risk model, an absolute risk model, or a combination of the two would be most appropriate in Harderian gland tumor risk calculations would depend on which of the above possibilities is most accurate.

NASA seeks to limit the risk of exposure-induced death (REID) from radiogenic cancer to below 3% (56). For multiple missions aboard the International Space Station (flown in solar minimum conditions), the model projects that males will exceed permissible exposure limits at 24 months and females, at 18 months; women are considered at greater risk for radiogenic cancers than men because of longer life spans and increased susceptibility to specific cancer types, including lung, ovarian, and breast carcinomas. Because the 3% REID is derived from the upper 95% confidence interval for the risk estimate (57), decreasing the uncertainty for space radiationinduced cancers can significantly increase the flight time allowed for astronauts. The 95% confidence interval surrounding the risk estimates not only primarily reflects uncertainties in our understanding of HZE ions but also includes uncertainties surrounding dose-rate effects, transfer of risk between human populations, space dosimetry, and errors in the existing human epidemiology data. Concerning sex predilections, our results also demonstrate a sex difference in carcinogenesis risk, where female mice are at greater risk for radiogenic cancers than males, following either HZE ion or -ray exposures. These results are consistent with the current NASA model to calculate cancer risk from space radiation exposures (5).

Whether genotypic assays of radiosensitivity can improve the precision of risk assessment in humans will depend on a number of factors. One is the extent to which heritable sequence variants determine cancer risk from HZE ion exposures. HZE ion radiation exposures result in more complex molecular lesions that are less amenable to repair (58). Thus, it could be argued that sequence variants that result in subtle differences in DNA repair and damage response pathways would have a lesser impact on HZE ion radiation carcinogenesis. However, this work demonstrates that genetic susceptibility does indeed have a significant role in tumorigenesis following HZE ion exposures. Personalized approaches to cancer risk assessments may eventually allow for greater reductions in uncertainties when generating space radiation cancer risk estimates (28).

There are limitations to a mouse carcinogenesis study comparing acute -ray and HZE ion exposures. First, for cost efficiency and logistics reasons, a single dose was used for each radiation quality: 3.0 Gy for -ray exposures and 0.4 Gy for HZE ion exposures. Preliminary studies have demonstrated that these doses produce the maximum tumor incidence in inbred strains (24). Because tumor susceptibility and association mapping were the primary goals of this study, doses were chosen with the goal of generating the greatest tumor incidences and, therefore, the greatest power to detect significant QTL. However, caution must be taken when comparing the two single-dose groups, as it is impossible to untangle dose responses in such a study. An additional benefit of the selected doses is that 0.4 Gy of HZE ions represents a realistic dose, received over 20 to 30 months, for a flight crew traveling to Mars. Second, the applicability of these findings to human populations is limited, as rodents serve only as models of carcinogenesis.

The results presented here indicate that host genetic factors dictate risk for tumor development following radiation exposures, regardless of radiation quality. Therefore, at a population level, risks can be extrapolated from terrestrial exposures to the space radiation environment and at an individual level, and humans harboring susceptibility alleles for radiation-induced tumors developed on Earth are also likely at increased risk in space.

Male and female HS/Npt mice (n = 1850) were generated from breeding pairs obtained from Oregon Health and Sciences University (Portland, OR). The mice were group-housed (five mice of the same sex per cage) in a climate-controlled facility at 70F (21.1C) with free access to food (Teklad global rodent diet 2918) and sterile water and a 12-hour light cycle. Mice were shipped to Brookhaven National Laboratories (Upton, NY) where they were exposed to accelerator-produced HZE ions at the NASA Space Radiation Laboratory at 7 to 12 weeks of age. HS/Npt stock mice of both sexes were exposed to 0.4 Gy of 28Si ions (240 MeV/n) (n = 308) or 56Fe ions (600 MeV/n) (n = 314), 3 Gy of 137Cs -rays (n = 615), or sham irradiated (n = 622). Following irradiation exposure or sham irradiations, mice were returned to Colorado State University (Fort Collins, CO) and monitored twice daily for the duration of the study. The mice were evaluated for cancer development until they reached 800 days of age or became moribund. All animal procedures were approved by the Colorado State University Institutional Animal Use and Care Committee.

This study uses a highly recombinant mouse population (HS/Npt stock) that is genetically diverse and designed for genome mapping (1921, 23). HS/Npt mice are a multiparent cross derived from eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J, and LP/J); each individual contains a unique mosaic of founder haplotypes and a high degree of heterozygosity, and recombination events become increasingly dense with each generation. Our population of HS/Npt mice was obtained from generation 71 of circular outbreeding.

DNA was isolated from tail biopsies taken from each mouse at 9 to 10 weeks of age. DNA was extracted and purified (QIAGEN, catalog no. 69506) according to the manufacturers instructions. GeneSeek (Lincoln, NE) performed genotyping assays using the Mega Mouse Universal Genotyping Array (MegaMUGA) (59) for a total of 1878 mice (including 28 inbred mice representing the founder strains). The MegaMUGA is built on the Illumina Infinium platform and consists of 77,808 single-nucleotide polymorphic markers that are distributed throughout the genome with an average spacing of 33 kb.

The heterogeneous stock mice are descendants of eight inbred founder strains. For each mouse, allele calls from the MegaMUGA array were used to calculate descent probabilities using a hidden Markov model (HMM), in which the hidden states were the founder strains and the observed data were the genotypes. The HMM generates probabilistic estimates of the diplotype state(s) for each marker locus and produces a unique founder haplotype mosaic for each mouse (18).

For this lifetime carcinogenesis study, all disease states were interpreted within the context of a systematic pathologic evaluation directed by board-certified veterinary pathologists (E.F.E. and D.A.K.). Structured necropsy and tissue collection protocols were followed for each mouse and involved photodocumentation of all gross lesions, collection of frozen tumor material, and preservation of tumor material in RNAlater. All tissues were grossly evaluated for all mice. To evaluate brain tissues and Harderian glands, craniums were decalcified for 48 hours in Formical-4 (StatLab, McKinney, TX 75069, product 1214) and five coronal sections of the skull were reviewed for each mouse. All gross lesions were evaluated microscopically and fixed in 10% neutral-buffered formalin and paraffin-embedded, and 5-m sections were stained with hematoxylin and eosin (H&E) and evaluated by a veterinary pathologist. For mice with solid tumors, all lung fields were examined histologically to detect the presence or absence of micrometastases. Tumor nomenclature was based on consensus statements produced by the Society of Toxicologic Pathology for mouse tumors (www.toxpath.org/inhand.asp). Representative histologic images routinely stained with H&E are presented in figs. S2 (A to E) and S3 (A and B).

Tissue microarrays were constructed to immunophenotype and subcategorize lymphoid neoplasms, which were the most commonly diagnosed tumors in irradiated and unirradiated HS/Npt mice. Identification of tissue sampling regions was performed by a veterinary pathologist. For each case, duplicate cores were taken from multiple anatomic locations (lymph nodes, spleen, thymus, etc.). Thirteen tissue microarrays were created, each of which contained six cores of control tissue at one corner of the array (haired skin, spleen, thymus, or liver); these control tissues were present in a unique combination and allowed for (i) orientation of the resulting sections, (ii) verification that the slide matched the block, and (iii) positive controls for immunohistochemistry. Figure S3D illustrates one tissue microarray as well as the resulting immunohistochemistry results for one thymic lymphoma (fig. S3E) and a core containing normal spleen (fig. S3F). Immunohistochemistry for T cell identification was performed using a rabbit monoclonal, anti-CD3 (SP7) antibody obtained from Abcam (ab16669; 1:300). Immunohistochemistry for B cell identification was performed using two rabbit monoclonal antibodies: an anti-CD45 antibody (ab10558; 1:1000) and an anti-PAX5 antibody (ab140341; 1:50). All immunohistochemistry was performed on a Leica BOND-MAX autostainer with the Leica BOND Polymer Refine Red Detection system (Leica DS9390, Newcastle Upon Tyne, UK). In addition to defining the immunophenotype, lymphomas were characterized according to the Mouse Model of Human Cancer Consortiums Bethesda protocols (60). For these protocols, anatomic location is important for the final diagnosis, and therefore, lymph node involvement was used from necropsy reports when necessary. Additional features included cell size, nuclear size, chromatic organization, and mitotic figure frequency, and the presence or absence of a leukemic phase was defined by bone marrow involvement within the sternum or femur. The most common lymphoma subtypes (fig. S4A) were evaluated for survival (fig. S4B), and pre-T LL typically presented with early-onset and large thymic masses.

Droplet digital polymerase chain reaction (ddPCR) was performed on cases of AML to assess deletion status via copy number variation for two genes: Spi1 and Asxl1. These genes are both located on chromosome 2 at base pair locations 91,082,390 to 91,115,756 for Spi1 and 153,345,845 to 153,404,007 for Asxl1. To establish a reference for normal diploid copy number in each AML sample, the copy number of H2afx was also determined. H2afx is located on chromosome 9, and deletions in this region have not been reported in murine AML. Bio-Rad PrimePCR probes were used for all assays as follows: Asxl1 ddPCR probe (dMmuCPE5100268), Spi1 ddPCR probe (dMmuCPE5094900), and H2afx ddPCR probe (dMmuCPE5104287). Ratios were created between the test gene and the reference gene (Spi1:H2afx and Asxl1:H2afx) to determine copy number with the assumption that the reference gene would not be deleted or amplified. Ideally, ratios of 1:1 represent equal copy numbers for both the test gene and the reference gene, and ratios of 1:2 represent a deletion in one copy of the test gene. However, since the tumor samples contained neoplastic cells as well as stromal cells and other cells, the ideal 1:2 ratio was not commonly observed. This is because stromal cells, which occur at unknown proportions in each tumor and which should not have chromosomal deletions, artificially increase ratios for tumor samples in which a deletion is indeed present. To account for stromal cell contamination, a cutoff ratio of 3:4 was established. Tumor samples with ratios below 3:4 were considered to have a deletion in one copy of the test gene.

For cases in which a solid tumor was identified, a standard section containing all lung lobes was processed and evaluated histologically. In cases where pulmonary metastases were observed, whole-slide scanning was performed at 200 magnification using an Olympus VS120-S5 and the OlyVIA software suite (www.olympusamerica.com/) to generate images for quantification of metastatic density (fig. S5). An analysis software, ImageJ (https://imagej.nih.gov/ij/), was used to quantify the total area of normal lung and the total area of metastatic foci (fig. S5). Metastatic density is reported as a percentage of the total metastasis area divided by the total lung area.

Association mapping was performed using a mixed-effects regression model with sex and cohort as fixed effects and a random-effects term to adjust for relatedness between mice by computing a matrix of expected allele sharing of founder haplotypes for each pair of mice (22). Three statistical models were fit to account for the wide range of trait distributions in this study. A generalized linear regression model was fit for binomial distributions, such as neoplasia. Cox regression analysis was incorporated to model time-to-event distributions to evaluate genetic contributions to tumor latency. Following genome-wide association analyses, resample model averaging methods were used to identify QTL that are consistently reproduced within subsamples of the mapping population.

Thresholds were determined using a permutation procedure in which the genotypes were fixed and the phenotype values were rearranged randomly within each sex. The distribution of the maximum negative log(P value) of association under the null hypothesis that no associations exist (null model) was determined for each genome scan with permuted data. One thousand permutations were performed for each phenotype in each radiation exposure group, simulating effects arising from covariates, the linkage disequilibrium structure of the genome, and effects due to phenotype distribution. A threshold was defined as an estimate of the genome-wide significance for which a type I statistical error will occur at a given frequency (29). Confidence intervals for each QTL were determined by nonparametric resample model averaging procedures using bootstrap aggregation with replacement. In this procedure, the mapping population is sampled to create a new dataset in which some individuals may be omitted and some may appear multiple times (30), and the locus with peak significance is recorded. Resampling is repeated 200 times for each phenotype to determine a 95% confidence interval for a given QTL. Effect sizes were calculated using the Tjur method for association mapping with logistic regression and pseudo-R2 for mapping with Cox proportional hazard regression. Statistical significance for each model was assessed using a permutation strategy to randomize genotypes via resampling without replacement and maintaining covariates. Permutation analysis was performed (1000 tests) for each trait and exposure group to generate estimations of genome-wide significance thresholds. As genome scans with hundreds of thousands of imputed SNPs are computationally intensive, parallel computing was essential and accomplished using spot instances of resizable Elastic Compute Cloud hosting resources.

Comparisons were made between whole-genome scans using Pearson correlations as a similarity measure with clustering based on average linkage. Significance of clustering results was estimated with 10,000 random permutations of the dataset (log10 values permuted with genetic markers) to determine a distribution of dendrogram heights under the null hypothesis that no associations exist. Each permutated dataset simulates a null distribution of the maximally significant clustering based on a randomly assorted set of P values for each genomic locus.

Bootstrap aggregation is a resample model averaging procedure that has been demonstrated to produce highly accurate estimates of QTL in structured populations (32). The procedure is relatively simple: for a genome-wide association study (GWAS) of n individuals, a sampling of n draws is obtained, with replacement, from the observed individuals to form a new dataset in which some individuals are omitted and some appear multiple times. For each new dataset created this way, an estimate of the QTL location is calculated. This process is repeated many times and is the basis for determining a confidence interval for a given result. The use of bootstrap procedures is commonly used this way to estimate QTL support intervals in experimental crosses; however, this statistical method can potentially be applied to other areas of QTL research, including comparative QTL mapping.

When an identical QTL is observed for two distinct traits, one explanation is that a single gene is involved for two distinct biologic processes, also known as pleiotropy. This was sometimes assumed in early mouse QTL studies that resulted in coincident loci for distinct traits. Another possibility, however, is that two distinct genetic variants are present in close proximity, each independently contributing to the two phenotypes. Because the two hypothetical genetic variants happen to be in close proximity, they are difficult to distinguish in low-resolution mapping studies. Using resample model averaging in highly recombinant mice is proposed to best differentiate precise locations of the QTL; if the same markers were repeatedly identified, then the case for pleiotropy was strengthened. For comparative QTL mapping in tumorigenesis studies, nonparametric resample model averaging could similarly be leveraged to identify whether the same QTL renders an individual susceptible to distinct environmental carcinogens. One significant advantage to using bootstrap procedures to detect potential coincident loci is that comparisons can be made between groups based on the identification of a highly significant QTL identified in only one exposure group (e.g., at a false-positive rate of 1 per 20 scans). This QTL may be present in the alternative exposure group, but at lower confidence (e.g., at a false-positive rate of 1 per 10 scans), and therefore discarded in a typical GWAS. A diagrammatic representation of the comparative QTL bootstrap procedure is presented in fig. S6. Because the resultant genetic positions derived from bootstrapping are composed of the most significant locus for each resampling regardless of the significance level for the mapping procedure, comparisons can be drawn between QTL that might have been discarded on the basis of the stringent statistical demands of an assay involving hundreds of thousands of independent tests. Using this procedure on thyroid tumors demonstrates that the same loci are consistently identified whether exposed to particle or photon irradiation (Fig. 2E). Using the comparative QTL procedure described, it can be determined whether an individuals cancer risk from one carcinogen will be predictive of that individuals cancer risk to another carcinogen. The application of this procedure is well illustrated by the space radiation problem, where much is known about -ray exposures and little is known about space radiation exposures.

In addition to looking for similarities between individual selected QTL for HZE ion and -rayexposed populations, we also sought a more holistic method in which entire genome scans could be compared between groups in an unsupervised process. By using entire genome scans, we submit for comparison not only highly significant regions but also the numerous loci detected with lower confidence. To determine similarity of genetic association profiles for all phenotypes and to detect possible coincident QTL, clustering procedures were used to compare genome-wide association scans between different radiation exposure groups. To demonstrate and validate the methodology of QTL clustering, genome-wide scans for coat colors in each treatment group are evaluated (Fig. 5B). As expected, genome-wide scans for coat color are unaffected by radiation exposures, and therefore, clustering is based entirely on coat phenotype rather than radiation exposure group. Using the same procedure for neoplasia indicates that tumor types often clustered together as well, regardless of radiation exposure (Fig. 5A). Genome scans for thyroid tumors and mammary adenocarcinomas in radiation-exposed groups and all hepatocellular carcinoma genome scans cluster together. This finding supports the hypothesis that host genetic factors are more important in determining neoplasm incidence than radiation exposure type. Unlike other statistic procedures, such as regression models, clustering lacks a response variable and is not routinely performed as a formal hypothesis test. Therefore, determining the significance of a clustering result can be problematic, as no consensus method exists for cluster validation. Permutation analysis provides the distribution of clustering results that will randomly occur from a given dataset; this can then be used as a baseline from which to determine a significance level on a given dendrogram tree [green line in Fig. 5 (A to C)]. While the overall validity of a given cluster can be accomplished by cluster permutation analysis, no method is identified to estimate the number of clusters that should be present in a dataset. Furthermore, methods to determine the significance of specific subset of objects clustering together do not exist; in such cases, the permutation threshold is likely overly stringent.

Excerpt from:
Genomic mapping in outbred mice reveals overlap in genetic susceptibility for HZE ion and -rayinduced tumors - Science Advances

NEW YORK and BASEL, Switzerland, April 15, 2020 (GLOBE NEWSWIRE) -- Axovant Gene Therapies Ltd., a clinical-stage company developing innovative gene therapies for neurological diseases, today announced its collaboration with Invitae, a leading medical genetics company, in the Detect Lysosomal Storage Diseases (Detect) program to facilitate faster diagnoses for children with lysosomal storage disorders (LSDs), including GM1 gangliosidosis and GM2 gangliosidosis, also known as Tay-Sachs/Sandhoff disease. Invitae offers genetic testing and counseling at no charge to patients suspected of having an LSD.

Axovant is committed to developing novel gene therapies for those living with rapidly progressive neurodegenerative diseases. We are hopeful that our collaboration with Invitae will provide families with easier access to genetic testing and bring us one step closer to identifying patients who may benefit from potential therapies, said Parag Meswani, PharmD., Axovants SVP of Commercial Strategy & Operations. Our AXO-AAV-GM1 clinical program targeting GM1 gangliosidosis is currently enrolling at the National Institutes of Health, and we are seeking IND clearance for the AXO-AAV-GM2 clinical trial targeting Tay-Sachs and Sandhoff diseases. Early intervention is ideal with potentially disease-modifying genetic therapies, and our diagnostics partnership with Invitae should allow us to identify and enroll children at even earlier stages of disease progression.

LSDs are progressive, multi-system, inherited metabolic diseases associated with premature death, and genetic testing is a crucial first step to arriving at a diagnosis. LSDs are misdiagnosed or undiagnosed in the majority of patients. The Detect program includes a specific LSD testing panel of 53 genes designed to provide patients and families accurate information quickly to preserve valuable treatment time.

Genetic testing can expedite an accurate diagnosis, facilitate earlier interventions, allow genetic counseling of family members, and support clinical research for LSDs such as GM1 and GM2 gangliosidosis, said Robert Nussbaum, M.D., chief medical officer of Invitae. Were pleased Axovant has joined the Detect program to help offer no-charge, sponsored genetic testing for those patients suspected of having the disease.

Research has shown no-charge testing programs with large well-designed panels help increase utilization of genetic testing, which can shorten the time to diagnosis by as much as 2 years in some conditions. Accurate diagnoses enable clinicians to focus on providing disease-specific care sooner, helping reduce costs and improve outcomes.

Additional details, as well as terms and conditions of the program, can be found at https://www.invitae.com/en/detectLSDs/.

About Axovant Gene Therapies

Axovant Gene Therapies is a clinical-stage gene therapy company focused on developing a pipeline of innovative product candidates for debilitating neurodegenerative diseases. Our current pipeline of gene therapy candidates targets GM1 gangliosidosis, GM2 gangliosidosis (including Tay-Sachs disease and Sandhoff disease), and Parkinsons disease. Axovant is focused on accelerating product candidates into and through clinical trials with a team of experts in gene therapy development and through external partnerships with leading gene therapy organizations. For more information, visit http://www.axovant.com.

About Invitae

Invitae Corporation (NYSE: NVTA) is a leading medical genetics company, whose mission is to bring comprehensive genetic information into mainstream medicine to improve healthcare for billions of people. Invitae's goal is to aggregate the world's genetic tests into a single service with higher quality, faster turnaround time, and lower prices. For more information, visit the company's website atinvitae.com.

Forward-Looking Statements

This press release contains forward-looking statements for the purposes of the safe harbor provisions under The Private Securities Litigation Reform Act of 1995 and other federal securities laws. The use of words such as "may," "might," "will," "would," "should," "expect," "believe," "estimate," and other similar expressions are intended to identify forward-looking statements. For example, all statements Axovant makes regarding costs associated with its operating activities are forward-looking. All forward-looking statements are based on estimates and assumptions by Axovants management that, although Axovant believes to be reasonable, are inherently uncertain. All forward-looking statements are subject to risks and uncertainties that may cause actual results to differ materially from those that Axovant expected. Such risks and uncertainties include, among others, the initiation and conduct of preclinical studies and clinical trials; the availability of data from clinical trials; the expectations for regulatory submissions and approvals; the continued development of its gene therapy product candidates and platforms; Axovants scientific approach and general development progress; and the availability or commercial potential of Axovants product candidates. These statements are also subject to a number of material risks and uncertainties that are described in Axovants most recent Quarterly Report on Form 10-Q filed with the Securities and Exchange Commission on February 10, 2020, as updated by its subsequent filings with the Securities and Exchange Commission. Any forward-looking statement speaks only as of the date on which it was made. Axovant undertakes no obligation to publicly update or revise any forward-looking statement, whether as a result of new information, future events or otherwise.

Media Contact:

Parag MeswaniAxovant Gene Therapies(212) 547-2523investors@axovant.commedia@axovant.com

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Axovant Announces Partnership with Invitae to Increase Access to Genetic Testing and Accelerate Diagnoses of GM1 and GM2 Gangliosidosis -...

Throughout history, the nations colleges and universities have set the foundation for innovation and social change. Weve uncovered the secrets of DNA. Weve unleashed bioengineering. We have harnessed intellectual power to create new technologyoften through the partnerships between land grant colleges and local industries and agriculturebringing the latest science to where it was needed. And we have done it all while demanding intellectual rigor and a sharp focus on the common good for society.

At Boston University, the Center for Regenerative Medicine at BUs Medical Center, alerted by colleagues at the University of Washington in Seattle, coordinated with MITs Broad Institute as well as Harvard to produce a test for the virus with a turn around time of within 24 hours. More than 50 volunteered in this round the clock effort. Testing is now underway. Rutgers University has launched its own virus testing program. Its RUCDR Infinite Biologicsa part of the Universitys Human Genetics Institute of New Jerseyis now capable of testing tens of thousands.

Tiny Bay Mills Community College, a Michigan tribal college of fewer than 500 students, has used 3-D technology to design and now produce 1,000 face masks for first responders every week.

Institutions of higher education, large and small, can and do play a significant role in serving our country and our world at this critical moment in history. But our work starts at home. Whats required is a community approach, as local areas are impacted in distinct ways while this crisis unfolds.

I learned the power of community response to overwhelming challenges at the American University of Nigeria. I served there as president when Boko Haram began to surge near the campus and federal assistance was nowhere to be found. The university brought the community together and kept the terrorist group at bay and fed refugees.

Drawing on that experience, when I arrived at Dickinson three years ago, I immediately began to gather with community members to identify their most pressing issues and to connect them with college resources. What started out as a dozen people has now grown to more than 50 representing nearly every sectornonprofits, school districts, health care, government and business. We are meeting remotely in the age of COVID-19, but the relationships we have built have allowed us to respond quickly in a coordinated manner to the communitys growing needs.

Working with Carlisle Borough, the Chamber of Commerce and Community CARES partnered to convert the Stuart Community Center into a shelter for the homeless. UPMC Carlisle anticipated a potential need for housing and shelter for its exhausted medical workers; Dickinson stepped up and agreed to make space available in our vacated residence halls. Local businesses needed an online presence to offer goods and services, but lacked the know-how; Dickinson students are developing e-commerce websites for those businesses. Our organic farm is supplying much-needed fresh produce for the community.

Colleges areand should beat the epicenter of community responses to COVID. They can and should be the assembly point for community action. Its imperative that colleges start building or strengthening relationships with leaders in their communities now, to help in recovery and before the next crisis or disaster occurs.

When students return to class, they will return to communities that have changed in myriad ways. The old ideas, approaches and leadership simply wont do. Our students and young people are the ones we will need to help us with the necessary reconstruction. Those students will rely on the knowledge and problem-solving skills our institutions of higher learning should be providing.

In these difficult times, the country must demand much of its colleges and universities. Communities must know that we are in the trenches with you, and that we are all of us prepared to do more. When students return to our campuses we should work together to build a program of national service. This is how we will rebuild America and prepare the next generation for more unprecedented challenges.

Margee M. Ensign is president of Dickinson College, in Carlisle. Previously, Ensign served as president of the American University of Nigeria, where she developed aid and relief programs for hundreds of thousands of internally displaced people fleeing Boko Haram.

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REYKJAVIK, Iceland, April 14, 2020 /PRNewswire/ -- Scientists at deCODE genetics and colleagues from Iceland's Directorate of Health and the National University Hospital today publish online in the New England Journal of Medicine a population-based study of the early spread of the SARS-Cov-2 virus (causing COVID-19 disease) in Iceland. The aim of the study was to provide as comprehensive a view as possible of how the virus spreads in a population, in this case one of 360,000 and implementing early and aggressive testing, tracking and isolation measures to contain the epidemic. The results show that roughly 0.8% of the population at large is infected with several strains or clades of the virus supporting the concern that silent carriers spread the disease. This suggests that while the efforts of the public health system have been effective so far in mitigating the spread to date, more data, including massive population screening, will be key to informing efforts to contain the virus in Iceland in the long run.

The study builds on combined targeted testing and population screening at more than 60,000 tests/million at April 4, the stop date for the data in this study; an additional 4,000 tests/million have been conducted in Iceland every day since that time. Icelandic health authorities began testing those returning from high-risk zones (mainly ski resorts in the Alps) and with likely symptoms in the beginning of February, a month before identifying the first SARS-Cov-2 infection on February 28. As of April 4, this targeted testing had identified 1221 cases from among 9199 symptomatic individuals and their contacts. All confirmed cases were placed in isolation and their contacts traced and put in 14-day home quarantine. To complement this testing and provide a view of the spread of the virus in the general population, on March 13 deCODE began testing volunteers who signed up for free screening. By April 1, 10797 people had been screened in this effort, with 87 (0.8%) testing positive. From April 1 to April 4, an additional 2,283 randomly selected individuals were screened, with 13 (0.6%) testing positive. Analysis of the combined testing data suggests that children and women are, in general, somewhat less susceptible to SARS-Cov-2 infection than men and adults.

"In attempting to carefully map the molecular epidemiology of COVID-19 in Iceland we hope to provide the entire world with data to use in the collective global effort to curb the spread of the disease," said Kari Stefansson, CEO of deCODE genetics and a senior author on the paper.

deCODE sequenced the virus from 643 individuals and drew a family tree of the different haplotypes (strings of sequence variants) found. Analysis of sequence data reveals that the haplotypes of the virus detected in the early targeted testing were almost entirely of the A2 clade originating in Austria and Italy and entering Iceland with people returning from skiing holidays. By contrast, the cases identified in the more recent targeted testing and in deCODE's population screening show that various haplotypes of the A1 clade prevalent in countries such as the UK had become more common, and that there is now a wide and growing variety of haplotypes present in the population.

This suggests that the virus entered Iceland from many countries, including those that were then deemed low-risk. Currently 291 mutations have been found in the country that have not been identified elsewhere. One of the utilities of the sequencing of the virus is that it makes it possible to track the contacts and additional infections coming from confirmed cases. These data, and the fact that the majority of new infections are coming from those already in quarantine, underscores the general efficacy of public health efforts to track and isolate these contacts and further control the spread of the virus.

"To bend the curve of this pandemic as quickly as possible, we need scientifically accurate information on how COVID-19 spreads in communities," said Robert A. Bradway, chairman and chief executive officer at Amgen. "I believe deCODE's swift response to this emergency and the insights they have generated will give give the rest of the world a stronger scientific foundation for public health decisions."

Based in Reykjavik, Iceland, deCODE is a global leader in analyzing and understanding the human genome. Using its unique expertise in human genetics combined with growing expertise in transcriptomics and population proteomics and vast amount of phenotypic data, deCODE has discovered risk factors for dozens of common diseases and provided key insights into their pathogenesis. The purpose of understanding the genetics of disease is to use that information to create new means of diagnosing, treating and preventing disease. deCODE is a wholly-owned subsidiary of Amgen (NASDAQ: AMGN).

Contact:

Thora Kristin Asgeirsdottir

PR and Communications

deCODE genetics

thoraa@decode.is

+354 894 1909

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More than five million Americans, mostly sixty-five or older, suffer from Alzheimers disease (AD), and that number is expected to triple by 2060, as todays twenty-somethings become seniors. No treatments exist for this devastating disease, and its root causes remain as tangled as the curious brain deformities that German physician Alois Alzheimer first described in 1906.

Now a team of Tufts researchers from the School of Medicine and the School of Engineering has received a five-year, $5 million grant from the National Institute on Aging, part of the National Institutes of Health, to study the role of different cell types and mutations in AD. They will use a unique bioengineered mini brain that realistically simulates the human brain environment for years.

The work, which builds on years of collaboration among the researchers, will overcome two traditional stumbling blocks to such studies: the limited relevance of animal models and the inability of cell culture systems to reproduce the physiology of the human brain. While age is the biggest risk factor for AD, genetics also plays a role. Scientists have uncovered twenty gene variants that increase the risk of AD, said Giuseppina Tesco, professor of neuroscience and lead investigator on the research, who has devoted her career to studying the disease.

Recent studies show that most of the genes that carry these variants are expressed in glial cells, particularly astrocytes and microglial cells. Once dismissed as onlookers in the brain, glia are now front and center in Alzheimers research said glia expert Philip Haydon, a principal investigator on the project. Haydon, the Annetta and Gustav Grisard Professor of Neuroscience, likens these cells to the pit crew for the flashy race-car-like neurons, supporting top performance by, for example, preventing buildup of protein plaques.

But unlike neurons, human glial cells behave very differently from those of other mammals. What we can learn from mouse models is very limited. It is very important to study these genes in human cells, said Tesco. And we need to do this over time. It may take months to see the effect of genetic variation.

The Tufts team will use cells derived from patients with AD as well as healthy subjects, drawing on advanced stem cell technology that makes it possible to reverse engineer human primary cells into induced pluripotent stem cells, which can then differentiate into neurons, astrocytes, and microglia.

These glia and other brain cells will grow on a unique three-dimensional doughnut-shaped scaffold made of porous silk and collagenwhat the researchers have dubbed a mini brain. Bioengineer David Kaplan, Stern Family Professor and a principal investigator on the grant, and his team have spent six years perfecting the mini brain for research on AD, traumatic brain injury, and brain cancer.

This model allows us to put cells where we want, determine ratios of different cells to use in the system, and control interactions, so we can study electrophysiology, synaptic activity, and other functions as the tissue ages, said Kaplan. That control over the long term supports exploration of age-related questions about disease progression and contributes to reproducibility, a scientific pillar. Past experiments using these mini brains have mimicked structural and functional features and neural activity for up to two years.

In contrast, a two-dimensional culture systemlike the proverbial petri dishwont replicate the complexities of multiple cell types and physiologies. And organoidssimplified organs in miniature now in vogueare subject to cellular death after a few weeks or months.

To complement the in vitro studies with the scaffolds, scientists in Haydons lab will transplant some of the human cells, both mutated and normal, into mice. As they grow, the human glia cells will replace the mouse cells, giving researchers an opportunity to study human brain function. This is the first step towards translational studies, said Haydon.

The grant complements donations from Tufts alumni, parents, friends, and other private individuals who have experienced the pain of Alzheimers disease in their own lives. Donor dollars really got some of our early, exploratory work up and running, said Haydon. Now we are building on that.

The NIH support is a bright spot at a time when COVID-19 has forced Tufts scientists, like their peers around the world, to halt laboratory research, sometimes losing years of work.

Tesco said that while it is difficult to be away from her lab, safety is more important than anything else. Im from Italy, where we have more than 22,000 deaths, she said. Being healthy and having the possibility to continue to do some work, I feel lucky. Well be in the best position possible when were ready to start because well be able to start something completely new and very exciting.

Kim Thurler can be reached at kimberly.thurler@tufts.edu.

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Stem Cells and Silk Make a New Way to Study the Brain - Tufts Now

EDISON, NJ A groundbreaking saliva test for the new coronavirus developed by researchers at Rutgers University's Human Genetics Institute one that uses patients' spit samples instead of a painful nasal swab has just been granted approval from the Food and Drug Administration and will go into use this week in New Jersey.

For the first time anywhere in the United States, the saliva tests will be offered to the general public starting Wednesday at the Edison Motor Vehicle Commission test site on Kilmer Road.

During his press conference on Tuesday, Gov. Phil Murphy suggested that the new testing could be part of the "robust" strategy New Jersey needs to help contain the coronavirus and, hopefully, help the state eventually reopen the economy. Read more: Gov. Murphy: NJ Coronavirus Outbreak Again Has Deadliest Day: 365

Rutgers said the White House's COVID-19 task force is working with the university to make these tests available nationwide.

Don't miss local and New Jersey announcements about the coronavirus. Sign up for Patch alerts and daily newsletters.

Middlesex County officials say that, to the best of their knowledge, the Edison location is the first test site in the nation to begin offering coronavirus saliva testing in a drive-thru setting.

To be tested at the Kilmer Road site, people must make an appointment in advance. More information on how to make an appointment and site hours is below. The testing is free.

The Rutgers scientists who invented the coronavirus saliva testing say the benefits are threefold. First, the test is less painful and less invasive than the existing test. Instead of having a swab far into the upper nasal cavity it's been described as excruciating patients now simply provide a spit sample into a test tube, in what the researchers call "spit and seal." Patients can also provide the spit-in-a-test tube sample themselves; they do not need to be taken by a healthcare worker.

Second, test results are much faster. Instead of three to five days, test results are available within 24 to 48 hours, a Middlesex County spokeswoman said. Third, because the saliva tests can be processed more quickly, more people can be tested in one day potentially up to 10,000 per day.

The coronavirus saliva tests were developed at Rutgers' RUCDR Infinite Biologics, led by chief operating officer Andrew Brooks, in partnership with Spectrum Solutions and Accurate Diagnostic Labs (ADL), both privately owned labs.

RUCDR Infinite Biologics is based in Piscataway and says it is the world's largest university-based cell and DNA repository. It is part of the Rutgers' Human Genetics Institute.

The saliva testing method is based on a Nobel Prize-winning laboratory technique that makes millions of copies of the SARS-CoV-2 virus nucleic acid (in this case RNA) in a sample.

As Patch reported, Rutgers unveiled the coronavirus saliva tests April 2. However, because the tests lacked FDA approval, it was only offered to patients and first responders doctors and nurses within the Robert Wood Johnson Barnabas Health network, a Rutgers partner.

However, this past weekend, the FDA granted what's known as "emergency use authorization" to give the saliva tests to the general public. It's the first time the FDA has given such emergency approval, according to a Rutgers news release. The FDA letter that gives emergency approval has been made publicly available, and it can be read it here.

According to the news release, the FDA approved the tests Saturday and, that same day, Brooks said he received a call from the White House's COVID-19 task force offering congratulations and asking how they could expand the saliva testing nationwide.

"The impact of this approval is significant," said Brooks, who also is a professor in the Rutgers genetics department. "It means we no longer have to put health care professionals at risk for infection by performing nasopharyngeal or oropharyngeal collections. We can preserve precious personal protective equipment for use in patient care instead of testing. We can significantly increase the number of people tested each and every day, as self-collection of saliva is more quick and scalable than swab collections. All of this combined will have a tremendous impact on testing in New Jersey and across the United States."

With that approval in hand, the saliva tests is to be rolled out to the Edison MVC test site starting Wednesday. The test tube samples will be analyzed by RUCDR Infinite Biologics at their Piscataway labs.

Two other start-up companies, MicroGen DX and Vault Health, are unveiling what they say are at-home saliva tests for coronavirus; Vault's test is available now on their website. RUCDR Infinite Biologics is also working with Vault to distribute their tests nationwide through telemedicine.

The saliva tests will only be available there Monday, Wednesday and Friday of each week. The Edison test site is at the Kilmer Vehicle Inspection/Driving Testing Center, a COVID-19 drive-thru testing facility on 33 Kilmer Road in Edison.

Brooks also predicted the sheer volume of samples that now can be tested will also help scientists come up with a coronavirus vaccine. The Rutgers RUCDR Infinite Biologics team is working to expand the coronavirus saliva testing nationwide.

The Edison test site was chosen because it is located very close to the Piscataway research labs of RUCDR Infinite Biologics. Middlesex County also already had the existing infrastructure and operational capabilities to introduce the new type of tests.

"We believe our state-of-the-art drive-thru model can set a benchmark for testing that can benefit the state and other counties," said Middlesex County Freeholder Director Ronald Rios. "Middlesex County has built the operations and infrastructure from the ground up to enable us to provide innovative solutions."

To get tested:

The criteria to get tested does not appear to have changed. First, you must be a Middlesex County resident (valid driver's license or state-issued identification is required); make an appointment online or via phone; and have either a valid doctor's prescription or be exhibiting symptoms that include a fever of 100.4 degrees or higher (99.6 degrees for people 65 years and older), respiratory symptoms and/or shortness of breath.

Middlesex County residents who have symptoms and would like to be tested should visit Middlesexcountynj.gov/COVID19testing to make an appointment. They will be assigned a time to report to the testing site.

Registrants must bring the completed registration form and proof of residency including, but not limited to: a valid driver's license; state issued identification; or two pieces of mail including utility bills, bank statements, or similar documentation with name and address, to the testing site.

If a resident does not have access to the internet or is having connectivity problems, they are instructed to call 732-745-3100 to make an appointment (from 10 a.m. to 4 p.m.). Appointments will only be made the day prior to a testing day.

If the person is not a Middlesex County resident, does not have a scheduled appointment or does not have symptoms, they will not receive testing.

Residents can visit the Middlesex County website at http://www.middlesexcountynj.gov/COVID-19 or contact 211 for information about the testing site, as well as call the Middlesex County Office of Health Services at 732-745-3100.

Residents who have questions about COVID-19 they can call 211 or the 24-hour public hotline at 800-962-1252 or 800-222-1222, or text NJCOVID to 898-211. They can also text a ZIP code to 898-211 for live text assistance.

Related:

Edison DMV Inspection Center Turned Into Coronavirus Test Site (March 30)

Rutgers Launches Fast-Results Saliva Testing For Coronavirus (April 2)

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NJ Site First In U.S. To Offer Drive-Thru Coronavirus Saliva Test - Patch.com

(Bloomberg Opinion) -- Scientists all over the world are working to understand, contain and cure Covid-19. Heres a quick look at four important advances that made headway this week.

A positive trial for an antiviral drug

Yesterday a rare bit of good news emerged from a clinical trial at the University of Chicago. STATnews reported that the antiviral drug Remdesivir appeared to have some fighting force against Covid-19. The trial included 125 people, 113 of them classified as having a severe case of the virus.

All got the drug; there was no placebo group. Most were released from the hospital less than a week later, and only 2 died an unusually low number given how deadly the disease has been in those who get severely ill. Other trials around the world, if they go this well, should lead to quick FDA approval for the drug, manufactured by Gilead Sciences.

Long before the current Covid-19 pandemic, scientists at the University of North Carolina and Gilead began developing this drug in anticipation of new coronavirus epidemic. Two other deadly outbreaks that occurred this century, SARS and MERS, were both caused by coronaviruses from bats, as with Covid-19.

One of the developers of the drug, Timothy Sheahan of the University of North Carolina, told me in an interview last January that the drug was designed to interfere with enzymes SARS and MERS need to replicate themselves. At the time, his group had just started to see impressive results in animal studies of MERS.

The only human trials before the current outbreak were in Ebola patients in the Democratic Republic of Congo. While it didnt work against Ebola as well as other therapies, it did pass basic safety standards.

The drug has been given sporadically for Covid-19. Anecdotal reports abound of people near death bouncing back after getting the drug. And even this clinical trial has to be viewed with cautious optimism, since it was small, and wasnt compared with a placebo. But more trials are underway around the world including 2,400 participants with severe disease and 1,600 patients whose symptoms are moderate.

New clues to how the virus spread from China

Genetic sleuths are digging deep into the origin and early spread of the Covid-19 virus, tracking small mutations in its genetic material. One surprise is that the virus had already branched into two subtypes by the time it was isolated from the first patient in Wuhan on December 23, and this patient seemed to have the second subtype not the original. Peter Forster, a genetics professor from Cambridge University, has dubbed the original variant A, and the one found in that Wuhan patient variant B. (B carries two mutations not found in A.)

Strain A is more than 96% identical to samples isolated from horseshoe bats, which he believes harbored the virus before it jumped to humans. A molecular clock technique puts that leap between September 18 and December 7, 2019.

Forster said he and his colleagues, who published their work in the Proceedings of the National Academy of Sciences, used a collection of published viral sequences collected in an international database normally used to track influenza. The paper only included the first 160 viral genomes, but his group has now studied more than 1,000.

Looking at data from before January 17, which represents the earliest date people started travelling for Chinese New Year, Forster found that of 44 Wuhan samples, 42 were B and only 2 were A. There were more A strains in the Guangdong Province in southern China.

Some people have speculated that the virus escaped from the Wuhan Institute of Virology, which may have been experimenting on coronaviruses, but Forester says his data point to a jump from bats in Southern China that subsequently spread to Wuhan and other areas. The B strain might have branched off before it reached Wuhan, where the first major outbreak was noticed.

Meanwhile, he says, they find viruses from cluster A in Americans whod travelled from China to the West Coast of the United States between January and early March. Before March 24th, most U.S. cases were A.

B, however, quickly became the dominant type in Wuhan and across China. Another mutation in B led to a strain C, which is nearly absent in China, but is still spreading across Europe. Europe has also shown a lot of sequences from the B cluster. (Whether these mutations affect the behavior or lethality of the virus is yet to be determined, since mutations dont always lead to changes in function.)

Story continues

Forster said the viral genetics show the first case in Italy in late January originated from an early spread in Germany, though Italian health authorities focused only on the patients possible connections to China. Meanwhile the disease is spreading uncontrolled across Italy.

Researchers at NYU and Mount Sinai used similar genetic information gathered later in the outbreak to determine that cases in New York City originated from multiple sources elsewhere in the U.S. and Europe, rather than directly from China, and that there had been local spread in New York for a month or so before it was officially first identified there at the end of February. Their paper is pending publication.

Forster hopes further work in sequencing genomes could help health authorities track new outbreaks without looking in the wrong place. And finding the true origin of the pandemic could help us avoid making the same mistake again.

Antibody studies are looking for more volunteers

Antibody tests have become a hot topic since people jumped to the conclusion that getting a positive test means you cant get or spread Covid-19. While standard tests detect genetic material from the virus itself, antibody tests can detect proteins the body makes to fight the infections.

New York Times tech columnist Kara Swisher wrote this week that she got one, because she knew a guy, but found it a moral dilemma to take a test so many others need.

It would have presented no moral dilemma had the guy been the head of a legitimate research project, because scientists still cant be sure antibodies from a previous infection always protect against a new one. Harvard epidemiologist Marc Lipsitch also warned that too little is yet known about post-infection immunity to assume people cant get re-infected.

Its hard to know what immunity to this virus looks like since its only been in humans since, maybe late 2019, says Harvard immunologist Duane Wesemann, who is collecting samples from volunteers to figure it out. Several other coronaviruses infect humans, causing a subset of common colds. Scientists want to know whether recent infection with these might affect the severity of Covid-19 infections.

The testing itself isnt rocket science, says Wesemann. But understanding the complex relationship between the virus and the human immune system is.

So far only about 6% of volunteers from around the Boston area were positive. Some reported a cold or sore throat in February or March, while others recalled no symptoms at all.

But the sample is still small.

Antibody-rich blood could help protect health care workers

If antibodies do work, and you test positive for them, you may be able to share your protection with several other people. Already, patients whove recovered from documented infections are donating their antibody-rich blood to others.

Doctors in China have treated small groups of patients and reported promising results in the Journal of the American Medical Association and the Proceeding of the National Academy of Sciences. In the United States, some severely ill patients get the same treatment under compassionate use guidelines.

But those are the cases where its least likely to work, says Johns Hopkins immunologist Arturo Casadevall. By then the virus has already done too much damage.

The rule of antibody therapy, he says, is it always works best if used early or prophylactically. Earlier this month, he and his fellow researchers at Johns Hopkins got approval for a clinical trial giving donated antibodies to front-line health care workers to protect them from getting sick.

Casadevall says he started pushing to develop the technology early, before the disease started spreading in the United States. His enthusiasm, he says, is based on his knowledge of medical history. Similar convalescent serum treatments have been used since the early 20th century to prevent or treat measles, mumps, and polio.

Unlike a vaccine, borrowed antibodies from recovered patients would confer only temporary protection starting to fade after a half-life of about 20 days. Still, thats long enough to help health care workers desperate to avoid getting infected.

The big limiting factor now is supply, he says. But that could change with more recovered patients and more antibody testing of people who had been only mildly ill. Donated blood can also be tested for antibodies.

Casadevall is optimistic that the biomedical research community will make quick inroads on this virus between new treatments, new ways to speed up testing, and ways to protect people before a vaccine is close.

While this is the worst pandemic since 1918, and governments in many countries were slow to take precautions, he believes the international biomedical research community is a mighty force. Humanity has never been better prepared.

This column does not necessarily reflect the opinion of Bloomberg LP and its owners.

Faye Flam is a Bloomberg Opinion columnist. She has written for the Economist, the New York Times, the Washington Post, Psychology Today, Science and other publications. She has a degree in geophysics from the California Institute of Technology.

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