Burkitt lymphoma research in East Africa : highlights from the 9th African organization for research and training in cancer conference held in Durban, South Africa in 2013

A one-day workshop on Burkitt lymphoma (BL) was held at the 9th African Organization for Research and Training in Cancer (AORTIC) conference in 2013 in Durban, South Africa. The workshop featured 15 plenary talks by delegates representing 13 institutions that either fund or implement research on BL targeting AORTIC delegates primarily interested in pediatric oncology. The main outcomes of the meeting were improved sharing of knowledge and experience about ongoing epidemiologic BL research, BL treatment in different settings, the role of cancer registries in cancer research, and opportunities for African scientists to publish in scientific journals. The idea of forming a consortium of BL to improve coordination, information sharing, accelerate discovery, dissemination, and translation of knowledge and to build capacity, while reducing redundant efforts was discussed. Here, we summarize the presentations and discussions from the workshop

IFNL4 Genotypes and Risk of Childhood Burkitt Lymphoma in East Africa.

Interferon lambda 4 (IFN-λ4) is a novel type-III interferon that can be expressed only by carriers of the genetic variant rs368234815-dG within the first exon of the IFNL4 gene. Genetic inability to produce IFN-λ4 (in carriers of the rs368234815-TT/TT genotype) has been associated with improved clearance of hepatitis C virus (HCV) infection. The IFN-λ4-expressing rs368234815-dG allele (IFNL4-dG) is most common (up to 78%) in West sub-Saharan Africa (SSA), compared to 35% of Europeans and 5% of individuals from East Asia. The negative selection of IFNL4-dG outside Africa suggests that its retention in African populations could provide survival benefits, most likely in children. To explore this hypothesis, we conducted a comprehensive association analysis between IFNL4 genotypes and the risk of childhood Burkitt lymphoma (BL), a lethal infection-associated cancer most common in SSA. We used genetic, epidemiologic, and clinical data for 4,038 children from the Epidemiology of Burkitt Lymphoma in East African Children and Minors (EMBLEM) and the Malawi Infections and Childhood Cancer case-control studies. Generalized linear mixed models fit with the logit link controlling for age, sex, country, P. falciparum infection status, population stratification, and relatedness found no significant association between BL risk and 3 coding genetic variants within IFNL4 (rs368234815, rs117648444, and rs142981501) and their combinations. Because BL occurs in children 6-9 years of age who survived early childhood infections, our results suggest that additional studies should explore the associations of IFNL4-dG allele in younger children. This comprehensive study represents an important baseline in defining the health effects of IFN-λ4 in African populations

Human leukocyte antigen-DQA1*04:01 and rs2040406 variants are associated with elevated risk of childhood Burkitt lymphoma

Burkitt lymphoma (BL) is responsible for many childhood cancers in sub-Saharan Africa, where it is linked to recurrent or chronic infection by Epstein-Barr virus or Plasmodium falciparum. However, whether human leukocyte antigen (HLA) polymorphisms, which regulate immune response, are associated with BL has not been well investigated, which limits our understanding of BL etiology. Here we investigate this association among 4,645 children aged 0-15 years, 800 with BL, enrolled in Uganda, Tanzania, Kenya, and Malawi. HLA alleles are imputed with accuracy >90% for HLA class I and 85-89% for class II alleles. BL risk is elevated with HLA-DQA1*04:01 (adjusted odds ratio [OR] = 1.61, 95% confidence interval [CI] = 1.32-1.97, P = 3.71 × 10-6), with rs2040406(G) in HLA-DQA1 region (OR = 1.43, 95% CI = 1.26-1.63, P = 4.62 × 10-8), and with amino acid Gln at position 53 versus other variants in HLA-DQA1 (OR = 1.36, P = 2.06 × 10-6). The associations with HLA-DQA1*04:01 (OR = 1.29, P = 0.03) and rs2040406(G) (OR = 1.68, P = 0.019) persist in mutually adjusted models. The higher risk rs2040406(G) variant for BL is associated with decreased HLA-DQB1 expression in eQTLs in EBV transformed lymphocytes. Our results support the role of HLA variation in the etiology of BL and suggest that a promising area of research might be understanding the link between HLA variation and EBV control

Mosaic chromosomal alterations in peripheral blood leukocytes of children in sub-Saharan Africa

In high-income countries, mosaic chromosomal alterations in peripheral blood leukocytes are associated with an elevated risk of adverse health outcomes, including hematologic malignancies. We investigate mosaic chromosomal alterations in sub-Saharan Africa among 931 children with Burkitt lymphoma, an aggressive lymphoma commonly characterized by immunoglobulin-MYC chromosomal rearrangements, 3822 Burkitt lymphoma-free children, and 674 cancer-free men from Ghana. We find autosomal and X chromosome mosaic chromosomal alterations in 3.4% and 1.7% of Burkitt lymphoma-free children, and 8.4% and 3.7% of children with Burkitt lymphoma (P-values = 5.7×10-11 and 3.74×10-2, respectively). Autosomal mosaic chromosomal alterations are detected in 14.0% of Ghanaian men and increase with age. Mosaic chromosomal alterations in Burkitt lymphoma cases include gains on chromosomes 1q and 8, the latter spanning MYC, while mosaic chromosomal alterations in Burkitt lymphoma-free children include copy-neutral loss of heterozygosity on chromosomes 10, 14, and 16. Our results highlight mosaic chromosomal alterations in sub-Saharan African populations as a promising area of research

A case-control study of Burkitt lymphoma in East Africa: are local health facilities an appropriate source of representative controls?

Abstract Background We investigated the feasibility and appropriateness of enrolling controls for Burkitt lymphoma (BL) from local health facilities in two regions in Uganda. Methods BL case data were compiled from two local hospitals with capacity to diagnose and treat BL in North-west and North-central regions of Uganda during 1997 to 2009. Local health facility data were compiled from children attending four representative local health facilities in the two regions over a two week period in May/June 2010. Age and sex patterns of BL cases and children at local facilities were compared and contrasted using frequency tables. Results There were 999 BL cases diagnosed in the study area (92% of all BL cases treated at the hospitals): 64% were from North-central and 36% from North-west region. The mean age of BL cases was 7.0 years (standard deviation [SD] 3.0). Boys were younger than girls (6.6 years versus 7.2 years, P = 0.004) and cases from North-central region were younger than cases from North-west region (6.8 years versus 7.3 years, P = 0.014). There were 1012 children recorded at the four local health facilities: 91% at facilities in North-central region and 9% from facilities in North-west region. Daily attendance varied between 1 to 75 children per day. The mean age of children at health facilities was 2.2 years (SD 2.8); it did not differ by sex. Children at North-central region facilities were younger than children at North-west region facilities (1.8 years versus 6.6 years, P < 0.001). Conclusions While many children attend local health facilities, confirming feasibility of obtaining controls, their mean age is much lower than BL cases. Health facilities may be suitable for obtaining young, but not older, controls

Age and geographic patterns of Plasmodium falciparum malaria infection in a representative sample of children living in Burkitt lymphoma-endemic areas of northern Uganda

BACKGROUND: Falciparum malaria is an important risk factor for African Burkitt lymphoma (BL), but few studies have evaluated malaria patterns in healthy BL-age children in populations where both diseases are endemic. To obtain accurate current data, patterns of asymptomatic malaria were investigated in northern Uganda, where BL is endemic. METHODS: Between 2011 and 2015, 1150 apparently healthy children under 15 years old were sampled from 100 villages in northern Uganda using a stratified, multi-stage, cluster survey design. Falciparum malaria prevalence (pfPR) was assessed by questionnaire, rapid diagnostic test (RDT) and thick film microscopy (TFM). Weighted pfPR and unadjusted and adjusted associations of prevalence with covariates were calculated using logistic models and survey methods. RESULTS: Based on 1143 children successfully tested, weighted pfPR was 54.8% by RDT and 43.4% by TFM. RDT sensitivity and specificity were 97.5 and 77.8%, respectively, as compared to TFM, because RDT detect malaria antigens, which persist in peripheral blood after clinical malaria, thus results based on RDT are reported. Weighted pfPR increased from 40% in children aged under 2 years to 61.8% in children aged 6–8 years (odds ratio 2.42, 95% confidence interval (CI) 1.26–4.65), then fell slightly to 49% in those aged 12–15 years. Geometric mean parasite density was 1805.5 parasites/µL (95% CI 1344.6–2424.3) among TFM-positive participants, and it was higher in children aged <5 years at 5092.9/µL (95% CI 2892.7–8966.8) and lower in those aged ≥10 years at 983.8/µL (95% CI 472.7–2047.4; P = 0.001). Weighted pfPR was lower in children residing in sub-regions employing indoor residual spraying (IRS) than in those residing in non-IRS sub-regions (32.8 versus 65.7%; OR 0.26, 95% CI 0.14, 0.46). However, pfPR varied both within IRS (3.2–55.3%) and non-IRS sub-regions (29.8–75.8%; Pheterogeneity <0.001). pfPR was inversely correlated with a child’s mother’s income (P = 0.011) and positively correlated with being enrolled in the wet season (P = 0.076), but sex was irrelevant. CONCLUSIONS: The study observed high but geographically and demographically heterogenous patterns of asymptomatic malaria prevalence among children living in northern Uganda. These results provide important baseline data that will enable precise evaluation of associations between malaria and BL. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12936-017-1778-z) contains supplementary material, which is available to authorized users

MOESM1 of A cross-sectional study of asymptomatic Plasmodium falciparum infection burden and risk factors in general population children in 12 villages in northern Uganda

Additional file 1: Table S1. Weighted distribution of characteristics of apparently healthy children aged 0–15 years enrolled between October 2011 and February 2014 in 12 villages in northern Uganda

MOESM1 of Age and geographic patterns of Plasmodium falciparum malaria infection in a representative sample of children living in Burkitt lymphoma-endemic areas of northern Uganda

Additional file 1

Genetic signatures of gene flow and malaria-driven natural selection in sub-Saharan populations of the "endemic Burkitt Lymphoma belt"

Submitted by Nuzia Santos ([email protected]) on 2020-02-04T14:35:16Z No. of bitstreams: 1 Genetic signatures of gene flow and malaria-driven.pdf: 11801795 bytes, checksum: fd87b07ab4fac498d62a72df070e920d (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2020-02-04T16:03:51Z (GMT) No. of bitstreams: 1 Genetic signatures of gene flow and malaria-driven.pdf: 11801795 bytes, checksum: fd87b07ab4fac498d62a72df070e920d (MD5)Made available in DSpace on 2020-02-04T16:03:51Z (GMT). No. of bitstreams: 1 Genetic signatures of gene flow and malaria-driven.pdf: 11801795 bytes, checksum: fd87b07ab4fac498d62a72df070e920d (MD5) Previous issue date: 2019Fundação Oswaldo Cruz. Instituto René Rachou. Belo Horizonte, MG, Brasil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia. Belo Horizonte, MG, Brasil /Center for Research on Genomics & Global Health, National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia. Belo Horizonte, MG, Brasil.Universidade de São Paulo. Instituto de Biociências. Departamento de Genética e Biologia Evolutiva. São Paulo, SP, Brasil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia. Belo Horizonte, MG, Brasil / Universidade Federal de Minas Gerais. Departamento de Estatística. Belo Horizonte, MG, Brasil.EMBLEM Study. African Field Epidemiology Network. Kampala, Uganda.University of Ghana Medical School, Accra, Ghana.University of Ghana Medical School, Accra, Ghana.EMBLEM Study. African Field Epidemiology Network. Kampala, Uganda.EMBLEM Study. African Field Epidemiology Network. Kampala, Uganda.EMBLEM Study. African Field Epidemiology Network. Kampala, Uganda.EMBLEM Study. African Field Epidemiology Network. Kampala, Uganda.Department of Biological Sciences. University of Botswana. Gaborone, Botswana.Department of Biomedical Sciences. University of Botswana School of Medicine. Gaborone, Botswana.EMBLEM Study. African Field Epidemiology Network. Kampala, Uganda.Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Division of Intramural Research. National Institute of Allergy and Infectious Diseases. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.University of Ghana Medical School. Accra, Ghana.University of Ghana Medical School. Accra, Ghana.University of Ghana Medical School. Accra, Ghana.University of Ghana Medical School. Accra, Ghana.Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Laboratory of Translational Genomics. Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. USDepartment of Health and Human Services. Bethesda, Maryland, USA.Laboratory of Translational Genomics. Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Cancer Genomics Research Laboratory. Leidos Biomedical Research. Frederick National Laboratory for Cancer Research. US Department of Health and Human Services. Frederick, Maryland, USA.Fundação Oswaldo Cruz. Instituto René Rachou. Belo Horizonte, MG, Brasil.Stanford Cancer Institute. Stanford University. Stanford, California, USA.Department of Genetics and Biology, University of Pennsylvania, Philadelphia, USA.Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Biologia Geral. Belo Horizonte, MG, Brasil.Division of Cancer Epidemiology and Genetics. National Cancer Institute. National Institutes of Health. US Department of Health and Human Services. Bethesda, Maryland, USA.Populations in sub-Saharan Africa have historically been exposed to intense selection from chronic infection with falciparum malaria. Interestingly, populations with the highest malaria intensity can be identified by the increased occurrence of endemic Burkitt Lymphoma (eBL), a pediatric cancer that affects populations with intense malaria exposure, in the so called “eBL belt” in sub-Saharan Africa. However, the effects of intense malaria exposure and sub-Saharan populations’ genetic histories remain poorly explored. To determine if historical migrations and intense malaria exposure have shaped the genetic composition of the eBL belt populations, we genotyped ~4.3 million SNPs in 1,708 individuals from Ghana and Northern Uganda, located on opposite sides of eBL belt and with ≥ 7 months/year of intense malaria exposure and published evidence of high incidence of BL. Among 35 Ghanaian tribes, we showed a predominantly West-Central African ancestry and genomic footprints of gene flow from Gambian and East African populations. In Uganda, the North West population showed a predominantly Nilotic ancestry, and the North Central population was a mixture of Nilotic and Southern Bantu ancestry, while the Southwest Ugandan population showed a predominant Southern Bantu ancestry. Our results support the hypothesis of diverse ancestral origins of the Ugandan, Kenyan and Tanzanian Great Lakes African populations, reflecting a confluence of Nilotic, Cushitic and Bantu migrations in the last 3000 years. Natural selection analyses suggest, for the first time, a strong positive selection signal in the ATP2B4 gene (rs10900588) in Northern Ugandan populations. These findings provide important baseline genomic data to facilitate disease association studies, including of eBL, in eBL belt populations