The predictive ability of the 313 variant–based polygenic risk score for contralateral breast cancer risk prediction in women of European ancestry with a heterozygous BRCA1 or BRCA2 pathogenic variant

Predicció de risc de càncer de mama; Dones europees; Variant patògena heterozigotaPredicción del riesgo de cáncer de mama; Mujeres europeas; Variante patógena heterocigotaBreast cancer risk prediction; European women; Heterozygous pathogenic variantPurpose To evaluate the association between a previously published 313 variant–based breast cancer (BC) polygenic risk score (PRS313) and contralateral breast cancer (CBC) risk, in BRCA1 and BRCA2 pathogenic variant heterozygotes. Methods We included women of European ancestry with a prevalent first primary invasive BC (BRCA1 = 6,591 with 1,402 prevalent CBC cases; BRCA2 = 4,208 with 647 prevalent CBC cases) from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA), a large international retrospective series. Cox regression analysis was performed to assess the association between overall and ER-specific PRS313 and CBC risk. Results For BRCA1 heterozygotes the estrogen receptor (ER)-negative PRS313 showed the largest association with CBC risk, hazard ratio (HR) per SD = 1.12, 95% confidence interval (CI) (1.06–1.18), C-index = 0.53; for BRCA2 heterozygotes, this was the ER-positive PRS313, HR = 1.15, 95% CI (1.07–1.25), C-index = 0.57. Adjusting for family history, age at diagnosis, treatment, or pathological characteristics for the first BC did not change association effect sizes. For women developing first BC < age 40 years, the cumulative PRS313 5th and 95th percentile 10-year CBC risks were 22% and 32% for BRCA1 and 13% and 23% for BRCA2 heterozygotes, respectively. Conclusion The PRS313 can be used to refine individual CBC risks for BRCA1/2 heterozygotes of European ancestry, however the PRS313 needs to be considered in the context of a multifactorial risk model to evaluate whether it might influence clinical decision-making

An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation

BACKGROUND PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. METHODS Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. RESULTS In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age of 40. CONCLUSIONS The PREDICT v2 is an improved prognostication and treatment benefit model compared with v1. The online version should continue to aid clinical decision making in women with early breast cancer

Evaluation of a system-specific function to describe the pharmacokinetics of benzylpenicillin in term neonates undergoing moderate hypothermia

The pharmacokinetic (PK) properties of intravenous (i.v.) benzylpenicillin in term neonates undergoing moderate hypothermia after perinatal asphyxia were evaluated, as they have been unknown until now. A system-specific modeling approach was applied, in which our recently developed covariate model describing developmental and temperature-induced changes in amoxicillin clearance (CL) in the same patient study population was incorporated into a population PK model of benzylpenicillin with a priori birthweight (BW)-based allometric scaling. Pediatric population covariate models describing the developmental changes in drug elimination may constitute system-specific information and may therefore be incorporated into PK models of drugs cleared through the same pathway. The performance of this system-specific model was compared to that of a reference model. Furthermore, Monte-Carlo simulations were performed to evaluate the optimal dose. The systemspecific model performed as well as the reference model. Significant correlations were found between CL and postnatal age (PNA), gestational age (GA), body temperature (TEMP), urine output (UO; system-specific model), and multiorgan failure (reference model). For a typical patient with a GA of 40 weeks, BW of 3, 000 g, PNA of 2 days (TEMP, 33.5°C), and normal UO (2 ml/kg/h), benzylpenicillin CL was 0.48 liter/h (interindividual variability [IIV] of 49%) and the volume of distribution of the central compartment was 0.62 liter/kg (IIV of 53%) in the system-specific model. Based on simulations, we advise a benzylpenicillin i.v. dose regimen of 75, 000 IU/kg/day every 8 h (q8h), 150, 000 IU/kg/day q8h, and 200, 000 IU/kg/day q6h for patients with GAs of 36 to 37 weeks, 38 to 41 weeks, and ≥42 weeks, respectively. Thesystem-specific model may be used for other drugs cleared through the same pathway accelerating model development

Identification of new genetic susceptibility loci for breast cancer through consideration of gene-environment interactions

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10(−07)), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m(2) (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m(2) or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10(−05)). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with prognosis of estrogen receptor-negative breast cancer after chemotherapy

Introduction: Tumor lymphocyte infiltration is associated with clinical response to chemotherapy in estrogen receptor (ER) negative breast cancer. To identify variants in immunosuppressive pathway genes associated with prognosis after adjuvant chemotherapy for ER-negative patients, we studied stage I-III invasive breast cancer patients of European ancestry, including 9,334 ER-positive (3,151 treated with chemotherapy) and 2,334 ER-negative patients (1,499 treated with chemotherapy). Methods: We pooled data from sixteen studies from the Breast Cancer Association Consortium (BCAC), and employed two independent studies for replications. Overall 3,610 single nucleotide polymorphisms (SNPs) in 133 genes were genotyped as part of the Collaborative Oncological Gene-environment Study, in which phenotype and clinical data were collected and harmonized. Multivariable Cox proportional hazard regression was used to assess genetic associations with overall survival (OS) and breast

Addressing climate change with behavioral science: a global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors

The predictive ability of the 313 variant–based polygenic risk score for contralateral breast cancer risk prediction in women of European ancestry with a heterozygous BRCA1 or BRCA2 pathogenic variant

Abstract: Purpose: To evaluate the association between a previously published 313 variant–based breast cancer (BC) polygenic risk score (PRS313) and contralateral breast cancer (CBC) risk, in BRCA1 and BRCA2 pathogenic variant heterozygotes. Methods: We included women of European ancestry with a prevalent first primary invasive BC (BRCA1 = 6,591 with 1,402 prevalent CBC cases; BRCA2 = 4,208 with 647 prevalent CBC cases) from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA), a large international retrospective series. Cox regression analysis was performed to assess the association between overall and ER-specific PRS313 and CBC risk. Results: For BRCA1 heterozygotes the estrogen receptor (ER)-negative PRS313 showed the largest association with CBC risk, hazard ratio (HR) per SD = 1.12, 95% confidence interval (CI) (1.06–1.18), C-index = 0.53; for BRCA2 heterozygotes, this was the ER-positive PRS313, HR = 1.15, 95% CI (1.07–1.25), C-index = 0.57. Adjusting for family history, age at diagnosis, treatment, or pathological characteristics for the first BC did not change association effect sizes. For women developing first BC < age 40 years, the cumulative PRS313 5th and 95th percentile 10-year CBC risks were 22% and 32% for BRCA1 and 13% and 23% for BRCA2 heterozygotes, respectively. Conclusion: The PRS313 can be used to refine individual CBC risks for BRCA1/2 heterozygotes of European ancestry, however the PRS313 needs to be considered in the context of a multifactorial risk model to evaluate whether it might influence clinical decision-making

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with prognosis of estrogen receptor-negative breast cancer after chemotherapy

Abstract Introduction Tumor lymphocyte infiltration is associated with clinical response to chemotherapy in estrogen receptor (ER) negative breast cancer. To identify variants in immunosuppressive pathway genes associated with prognosis after adjuvant chemotherapy for ER-negative patients, we studied stage I-III invasive breast cancer patients of European ancestry, including 9,334 ER-positive (3,151 treated with chemotherapy) and 2,334 ER-negative patients (1,499 treated with chemotherapy). Methods We pooled data from sixteen studies from the Breast Cancer Association Consortium (BCAC), and employed two independent studies for replications. Overall 3,610 single nucleotide polymorphisms (SNPs) in 133 genes were genotyped as part of the Collaborative Oncological Gene-environment Study, in which phenotype and clinical data were collected and harmonized. Multivariable Cox proportional hazard regression was used to assess genetic associations with overall survival (OS) and breast cancer-specific survival (BCSS). Heterogeneity according to chemotherapy or ER status was evaluated with the log-likelihood ratio test. Results Three independent SNPs in TGFBR2 and IL12B were associated with OS (P  C) (per allele hazard ratio (HR) 1.54 (95% confidence interval (CI) 1.22 to 1.95), P = 3.08 × 10−4) was not found in ER-negative patients without chemotherapy or ER-positive patients with chemotherapy (P for interaction  A) with poorer OS (HR 1.50 (95% CI 1.21 to 1.86), P = 1.81 × 10−4), and rs2853694 (A > C) with improved OS (HR 0.73 (95% CI 0.61 to 0.87), P = 3.67 × 10−4). Similar associations were observed with BCSS. Association with TGFBR2 rs1367610 but not IL12B variants replicated using BCAC Asian samples and the independent Prospective Study of Outcomes in Sporadic versus Hereditary Breast Cancer Study and yielded a combined HR of 1.57 ((95% CI 1.28 to 1.94), P = 2.05 × 10−5) without study heterogeneity. Conclusions TGFBR2 variants may have prognostic and predictive value in ER-negative breast cancer patients treated with adjuvant chemotherapy. Our findings provide further insights into the development of immunotherapeutic targets for ER-negative breast cancer

The predictive ability of the 313 variant–based polygenic risk score for contralateral breast cancer risk prediction in women of European ancestry with a heterozygous BRCA1 or BRCA2 pathogenic variant

PURPOSE : To evaluate the association between a previously published 313 variant–based breast cancer (BC) polygenic risk score (PRS313) and contralateral breast cancer (CBC) risk, in BRCA1 and BRCA2 pathogenic variant heterozygotes. METHODS : We included women of European ancestry with a prevalent first primary invasive BC (BRCA1 = 6,591 with 1,402 prevalent CBC cases; BRCA2 = 4,208 with 647 prevalent CBC cases) from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA), a large international retrospective series. Cox regression analysis was performed to assess the association between overall and ER-specific PRS313 and CBC risk. RESULTS : For BRCA1 heterozygotes the estrogen receptor (ER)-negative PRS313 showed the largest association with CBC risk, hazard ratio (HR) per SD = 1.12, 95% confidence interval (CI) (1.06–1.18), C-index = 0.53; for BRCA2 heterozygotes, this was the ER-positive PRS313, HR= 1.15, 95% CI (1.07–1.25), C-index = 0.57. Adjusting for family history, age at diagnosis, treatment, or pathological characteristics for the first BC did not change association effect sizes. For women developing first BC < age 40 years, the cumulative PRS313 5th and 95th percentile 10-year CBC risks were 22% and 32% for BRCA1 and 13% and 23% for BRCA2 heterozygotes, respectively. CONCLUSION : The PRS313 can be used to refine individual CBC risks for BRCA1/2 heterozygotes of European ancestry, however the PRS313 needs to be considered in the context of a multifactorial risk model to evaluate whether it might influence clinical decisionmaking.This work was supported by the Alpe d’HuZes/Dutch Cancer Society (KWF Kankerbestrijding) project 6253 and Dutch Cancer Society (KWF Kankerbestrijding) project UL2014-7473. CIMBA: The CIMBA data management and data analysis were supported by Cancer Research–UK grants C12292/A20861, C12292/A11174. G.C.T. and A.B.S. are NHMRC Research Fellows. iCOGS: the European Community’s Seventh Framework Programme under grant agreement number 223175 (HEALTH-F2-2009- 223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/ A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/ A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112–the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer (CRN- 87521), and the Ministry of Economic Development, Innovation and Export Trade (PSR-SIIRI-701), Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. OncoArray: the PERSPECTIVE and PERSPECTIVE I&I projects funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministère de l’Économie, de la Science et de l’Innovation du Québec through Genome Québec, and the Quebec Breast Cancer Foundation; the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118 and C1287/A16563). BCFR: UM1 CA164920 from the National Cancer Institute. The content of this paper does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. BFBOCC: Lithuania (BFBOCC-LT): Research Council of Lithuania grant SEN-18/2015. BIDMC: Breast Cancer Research Foundation. BMBSA: Cancer Association of South Africa (PI Elizabeth J. van Rensburg). BRI-COH: S. L.N. is partially supported by the Morris and Horowitz Families Professorship. CNIO: Spanish Ministry of Health PI16/00440 supported by FEDER funds, the Spanish Ministry of Economy and Competitiveness (MINECO) SAF2014-57680-R and the Spanish Research Network on Rare diseases (CIBERER). COH-CCGCRN: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under grant number R25CA112486, and RC4CA153828 (PI: J. Weitzel) from the National Cancer Institute and the Office of the Director, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. CONSIT TEAM: Associazione Italiana Ricerca sul Cancro (AIRC; IG2015 number 16732) to P. Peterlongo. DEMOKRITOS: European Union (European Social Fund–ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)–Research Funding Program of the General Secretariat for Research & Technology: SYN11_10_19 NBCA. Investing in knowledge society through the European Social Fund. DFKZ: German Cancer Research Center. EMBRACE: Cancer Research UK Grants C1287/A10118 and C1287/A11990. D.G.E. and F.L. are supported by an NIHR grant to the Biomedical Research Centre, Manchester. The Investigators at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. R.E. and E.B. are supported by Cancer Research UK Grant C5047/A8385. R.E. is also supported by NIHR support to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. FCCC: A.K.G. was in part funded by the NCI (R01 CA214545), The University of Kansas Cancer Center Support Grant (P30 CA168524), The Kansas Institute for Precision Medicine (P20 GM130423), and the Kansas Bioscience Authority Eminent Scholar Program. A.K.G. is the Chancellors Distinguished Chair in Biomedical Sciences Professorship. FPGMX: A. Vega is supported by the Spanish Health Research Foundation, Instituto de Salud Carlos III (ISCIII), partially supported by FEDER funds through Research Activity Intensification Program (contract grant numbers: INT15/ 00070, INT16/00154, INT17/00133), and through Centro de Investigación Biomédica en Red de Enferemdades Raras CIBERER (ACCI 2016: ER17P1AC7112/2018); Autonomous Government of Galicia (Consolidation and structuring program: IN607B), and by the Fundación Mutua Madrileña. The German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) is funded by the German Cancer Aid (110837, 70111850, coordinator: Rita K. Schmutzler, Cologne) and the Ministry for Innovation, Science and Research of the State of North Rhine-Westphalia (#323- 8.0302.16.02-132142). GEMO: initially funded by the French National Institute of Cancer (INCa, PHRC Ile de France, grant AOR 01 082, 2001-2003, grant 2013-1-BCB-01- ICH-1), the Association “Le cancer du sein, parlons-en!” Award (2004), the Association for International Cancer Research (2008-2010), and the Foundation ARC pour la recherche sur le cancer (grant PJA 20151203365). It also received support from the Canadian Institute of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program (2008–2013), and the European commission FP7, Project «Collaborative Ovarian, breast and prostate Gene-environment Study (COGS), Large-scale integrating project» (2009–2013). GEMO is currently supported by the INCa grant SHS-E-SP 18-015. GEORGETOWN: The Survey, Recruitment, and Biospecimen Collection Shared Resource at Georgetown University (NIH/NCI grant P30- CA051008), the Fisher Center for Hereditary Cancer and Clinical Genomics Research, and the Nina Hyde Center for Breast Cancer Research. G-FAST: Bruce Poppe is a senior clinical investigator of FWO. Mattias Van Heetvelde obtained funding from IWT. HCSC: Spanish Ministry of Health PI15/00059, PI16/01292, and CB-161200301 CIBERONC from ISCIII (Spain), partially supported by European Regional Development FEDER funds. HEBCS: Helsinki University Hospital Research Fund, the Finnish Cancer Society and the Sigrid Juselius Foundation. The HEBON study is supported by the Dutch Cancer Society grants NKI1998-1854, NKI2004-3088, NKI2007-3756, the Netherlands Organisation of Scientific Research grant NWO 91109024, the Pink Ribbon grants 110005 and 2014-187.WO76, the BBMRI grant NWO 184.021.007/CP46 and the Transcan grant JTC 2012 Cancer 12-054. HRBCP: Hong Kong Sanatorium and Hospital, Dr Ellen Li Charitable Foundation, The Kerry Group Kuok Foundation, National Institute of Health1R 03CA130065, and North California Cancer Center. HUNBOCS: Hungarian Research Grants KTIA-OTKA CK-80745, NKFI_OTKA K-112228 and TUDFO/51757/2019-ITM. ICO: Contract grant sponsor: Supported by the Carlos III National Health Institute funded by FEDER funds–a way to build Europe–(PI16/00563, PI19/00553 and CIBERONC); the Government of Catalonia (Pla estratègic de recerca i innovació en salut (PERIS) Project MedPerCan, 2017SGR1282 and 2017SGR496); and CERCA program.IHCC: supported by grant PBZ_KBN_122/P05/2004 and the program of the Minister of Science and Higher Education under the name “Regional Initiative of Excellence” in 2019–2022 project number 002/RID/2018/19 amount of financing 12 000 000 PLN. ILUH: Icelandic Association “Walking for Breast Cancer Research” and by the Landspitali University Hospital Research Fund. INHERIT: Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program–grant CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade–grant # PSR-SIIRI-701. IOVHBOCS: Ministero della Salute and “5×1000” Istituto Oncologico Veneto grant. IPOBCS: Liga Portuguesa Contra o Cancro. kConFab: The National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. KOHBRA: the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 1020350; 1420190). KUMC: NIGMS P20 GM130423 (to A.K.G.). MAYO: NIH grants CA116167, CA192393 and CA176785, an NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), and a grant from the Breast Cancer Research Foundation. MCGILL: Jewish General Hospital Weekend to End Breast Cancer, Quebec Ministry of Economic Development, Innovation and Export Trade. Marc Tischkowitz is supported by the funded by the European Union Seventh Framework Program (2007Y2013)/European Research Council (Grant No. 310018). MODSQUAD: MH CZ–DRO (MMCI, 00209805) and LM2018125, MEYS–NPS I–LO1413 to LF, and by Charles University in Prague project UNCE204024 (MZ). MSKCC: the Breast Cancer Research Foundation, the Robert and Kate Niehaus Clinical Cancer Genetics Initiative, the Andrew Sabin Research Fund and a Cancer Center Support Grant/Core Grant (P30 CA008748). NAROD: 1R01 CA149429-01. NCI: the Intramural Research Program of the US National Cancer Institute, NIH, and by support services contracts NO2-CP-11019-50, N02-CP-21013-63 and N02-CP-65504 with Westat, Inc, Rockville, MD. NICCC: Clalit Health Services in Israel, the Israel Cancer Association and the Breast Cancer Research Foundation (BCRF), NY. NNPIO: the Russian Foundation for Basic Research (grants 17-00-00171, 18-515-45012 and 19-515-25001). NRG Oncology: U10 CA180868, NRG SDMC grant U10 CA180822, NRG Administrative Office and the NRG Tissue Bank (CA 27469), the NRG Statistical and Data Center (CA 37517) and the Intramural Research Program, NCI. OSUCCG: Ohio State University Comprehensive Cancer Center. PBCS: supported by the “Fondazione Pisa per la Scienza, project nr. 127/2016. Maria A Caligo was supported by the grant: “n. 127/16 Caratterizzazione delle varianti missenso nei geni BRCA1/2 per la valutazione del rischio di tumore al seno” by Fondazione Pisa, Pisa, Italy; SEABASS: Ministry of Science, Technology and Innovation, Ministry of Higher Education (UM.C/HlR/MOHE/ 06) and Cancer Research Initiatives Foundation. SMC: the Israeli Cancer Association. SWE-BRCA: the Swedish Cancer Society. UCHICAGO: NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA125183), R01 CA142996, 1U01CA161032 and by the Ralph and Marion Falk Medical Research Trust, the Entertainment Industry Fund National Women’s Cancer Research Alliance and the Breast Cancer research Foundation. O.I.O. is an ACS Clinical Research Professor. UCLA: Jonsson Comprehensive Cancer Center Foundation; Breast Cancer Research Foundation. UCSF: UCSF Cancer Risk Program and Helen Diller Family Comprehensive Cancer Center. UKFOCR: Cancer Research h UK. UPENN: Breast Cancer Research Foundation; Susan G. Komen Foundation for the cure, Basser Research Center for BRCA. UPITT/MWH: Hackers for Hope Pittsburgh. VFCTG: Victorian Cancer Agency, Cancer Australia, National Breast Cancer Foundation. WCP: B.Y.K. is funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), grant UL1TR000124.https://www.gimjournal.org/am2023Genetic

Genomic investigations of unexplained acute hepatitis in children

Since its first identification in Scotland, over 1,000 cases of unexplained paediatric hepatitis in children have been reported worldwide, including 278 cases in the UK1. Here we report an investigation of 38 cases, 66 age-matched immunocompetent controls and 21 immunocompromised comparator participants, using a combination of genomic, transcriptomic, proteomic and immunohistochemical methods. We detected high levels of adeno-associated virus 2 (AAV2) DNA in the liver, blood, plasma or stool from 27 of 28 cases. We found low levels of adenovirus (HAdV) and human herpesvirus 6B (HHV-6B) in 23 of 31 and 16 of 23, respectively, of the cases tested. By contrast, AAV2 was infrequently detected and at low titre in the blood or the liver from control children with HAdV, even when profoundly immunosuppressed. AAV2, HAdV and HHV-6 phylogeny excluded the emergence of novel strains in cases. Histological analyses of explanted livers showed enrichment for T cells and B lineage cells. Proteomic comparison of liver tissue from cases and healthy controls identified increased expression of HLA class 2, immunoglobulin variable regions and complement proteins. HAdV and AAV2 proteins were not detected in the livers. Instead, we identified AAV2 DNA complexes reflecting both HAdV-mediated and HHV-6B-mediated replication. We hypothesize that high levels of abnormal AAV2 replication products aided by HAdV and, in severe cases, HHV-6B may have triggered immune-mediated hepatic disease in genetically and immunologically predisposed children