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A Custom Genotyping Array Reveals Population-Level Heterogeneity for the Genetic Risks of Prostate Cancer and Other Cancers in Africa
Abstract
Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. Samples from Ghana and Nigeria clustered together, whereas samples from Senegal and South Africa yielded distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores for prostate cancer were higher in Nigeria than in Senegal. In summary, individual and population-level differences in prostate cancer risk were revealed using a novel genotyping array.
Significance
This study presents an Africa-specific genotyping array, which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers.
... (399 cases, 403 controls; >1.5 million custom markers) 13 . Furthermore, studies associating rare variants with PCa pathogenesis within Sub-Saharan Africa are equally scarce. ...
... 4 . Study references: a Cook et al. 10 , b Harlemon et al. 13 , c Tindall et al. 12 , d Du et al. 11 . B Admixture plot (K = 5, cross-validation error = 0.162) which was replicated in 10 out of 10 runs, including 1003 Africans, 20 Europeans, 20 Chinese individuals from the HGDP and 1KGP subset of gnomAD with our dataset of 781 South Africans. ...
... 68 additional resources are becoming available, although the pace remains a fraction of the global effort. As with the exomic-array used in this study 69 , commercial genotyping arrays have been designed based on variant frequencies heavily skewed towards Europeans, with arrays from MADCaP and H3Africa tailored for African populations, with the MADCaP array specifically designed for PCa research 13,68 . Furthermore, GREML analyses showed that only 49.71% (±22.71%) of the variance in phenotype could be explained by the autosomal genomic variance, indicating that the genomic risk for PCa was not fully captured by the European-biased exome array. ...
African ancestry is a significant risk factor for prostate cancer and advanced disease. Yet, genetic studies have largely been conducted outside the context of Sub-Saharan Africa, identifying 278 common risk variants contributing to a multiethnic polygenic risk score, with rare variants focused on a panel of roughly 20 pathogenic genes. Based on this knowledge, we are unable to determine polygenic risk or differentiate prostate cancer status interrogating whole genome data for 113 Black South African men. To further assess for potentially functional common and rare variant associations, here we interrogate 247,780 exomic variants for 798 Black South African men using a case versus control or aggressive versus non-aggressive study design. Notable genes of interest include HCP5, RFX6 and H3C1 for risk, and MKI67 and KLF5 for aggressive disease. Our study highlights the need for further inclusion across the African diaspora to establish African-relevant risk models aimed at reducing prostate cancer health disparities.
... West African individuals are found on the left of each multidimensional scaling (MDS) plot, and South African individuals are found on the bottom right of each MDS plot (Fig. 1a). This observed population structure is broadly consistent with a pilot study from the MADCaP Network [48]. An ADMIXTURE plot Fig. 1b). ...
... CaP cases and controls were frequency matched by age and study site. African individuals were genotyped using the MADCaP Array, a custom genotyping platform optimized for detecting genetic associations with prostate cancer in sub-Saharan African populations [48]. Details about sample accrual can be found in Andrews et al. [47], and details about SNP calling and QC filtering be found in Harlemon et al. [48]. ...
... African individuals were genotyped using the MADCaP Array, a custom genotyping platform optimized for detecting genetic associations with prostate cancer in sub-Saharan African populations [48]. Details about sample accrual can be found in Andrews et al. [47], and details about SNP calling and QC filtering be found in Harlemon et al. [48]. MADCaP samples were excluded if marker missingness exceeded 5%. ...
Background
Genome-wide association studies do not always replicate well across populations, limiting the generalizability of polygenic risk scores (PRS). Despite higher incidence and mortality rates of prostate cancer in men of African descent, much of what is known about cancer genetics comes from populations of European descent. To understand how well genetic predictions perform in different populations, we evaluated test characteristics of PRS from three previous studies using data from the UK Biobank and a novel dataset of 1298 prostate cancer cases and 1333 controls from Ghana, Nigeria, Senegal, and South Africa.
Results
Allele frequency differences cause predicted risks of prostate cancer to vary across populations. However, natural selection is not the primary driver of these differences. Comparing continental datasets, we find that polygenic predictions of case vs. control status are more effective for European individuals (AUC 0.608–0.707, OR 2.37–5.71) than for African individuals (AUC 0.502–0.585, OR 0.95–2.01). Furthermore, PRS that leverage information from African Americans yield modest AUC and odds ratio improvements for sub-Saharan African individuals. These improvements were larger for West Africans than for South Africans. Finally, we find that existing PRS are largely unable to predict whether African individuals develop aggressive forms of prostate cancer, as specified by higher tumor stages or Gleason scores.
Conclusions
Genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original GWAS. PRS built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities.
... We present results of PRS development for prostate cancer risk in non-European populations, such as African [47,48] and Latino [46] ethnicities in Table 2. Harlemon et al. [47] showed that a 139-SNP PRS exhibited a much higher prediction risk for prostate cancer in African than in European prostate cancer patients. In addition to heterogeneity between continental ethnicities, intra-ethnic analyzes identified that African subpopulations also demonstrated differences in risk for prostate cancer using the same PRS. ...
... We present results of PRS development for prostate cancer risk in non-European populations, such as African [47,48] and Latino [46] ethnicities in Table 2. Harlemon et al. [47] showed that a 139-SNP PRS exhibited a much higher prediction risk for prostate cancer in African than in European prostate cancer patients. In addition to heterogeneity between continental ethnicities, intra-ethnic analyzes identified that African subpopulations also demonstrated differences in risk for prostate cancer using the same PRS. ...
... In addition to heterogeneity between continental ethnicities, intra-ethnic analyzes identified that African subpopulations also demonstrated differences in risk for prostate cancer using the same PRS. For example, individuals from Senegal and Nigeria had a lower and higher predicted risk of prostate cancer, respectively, when compared to other African regions [47]. In an African Ugandan population, Du et al. [48] estimated the effect of known risk alleles using a PRS based on 97-SNPs in prostate cancer patients of this ancestry [42] and observed that the PRS score average was significantly higher for prostate cancer patients when compared to the control group (6.70 versus 6.25). ...
The development of new screening methods and diagnostic tests for traits, common diseases, and cancer is linked to the advent of precision genomic medicine, in which health care is individually adjusted based on a person’s lifestyle, environmental influences, and genetic variants. Based on genome-wide association study (GWAS) analysis, rapid and continuing progress in the discovery of relevant single nucleotide polymorphisms (SNPs) for traits or complex diseases has increased interest in the potential application of genetic risk models for routine health practice. The polygenic risk score (PRS) estimates an individual’s genetic risk of a trait or disease, calculated by employing a weighted sum of allele counts combined with non-genetic variables. However, 98.38% of PRS records held in public databases relate to the European population. Therefore, PRSs for multiethnic populations are urgently needed. We performed a systematic review to discuss the role of polygenic risk scores in advancing precision medicine for different cancer types in multiethnic non-European populations.
... In this investigation, we evaluated the previously developed multi-ancestry PRS in large independent samples of men from the Veteran Affairs Million Veteran Program (MVP; 21,078 cases and 284,177 controls, including 13,643 cases and 210,214 controls of European ancestry, 6353 cases and 53,362 controls of African ancestry, and 1082 cases and 20,601 controls from Hispanic populations) (Gaziano et al., 2016), the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network (405 cases and 396 controls of African ancestry) (Harlemon et al., 2020), and the Maryland Prostate Cancer Case-Control Study (NCI-MD; 383 cases and 395 controls of African ancestry) (Smith et al., 2017;'Methods'). We also included, through meta-analysis, independent replication studies of the multi-ancestry PRS conducted to date in European (UK Biobank and Mass General Brigham [MGB] Biobank) and African ancestry populations (California and Uganda Prostate Cancer Study [CA UG] and MGB Biobank; 'Methods'; Conti et al., 2021;Plym et al., 2022), bringing the total sample to 31,925 cases and 490,507 controls. ...
... The MADCaP Network dataset included 405 prostate cancer cases and 396 controls from sub-Saharan Africa, as previously described (Harlemon et al., 2020;Andrews et al., 2018), with a substantial proportion of cases diagnosed at late stages. The study protocol was approved by each study site's Institutional Review Board/Ethnic Review Board. ...
... Written informed consent was obtained from all participants, and studies were conducted in concordance with the Declaration of Helsinki and the U.S. Common Rule. The MADCaP samples were genotyped on a customized array designed to capture common genetic variation in diverse African populations, and genotyping and quality control have been described in detail elsewhere (Harlemon et al., 2020). GWAS data were imputed using the 1000 Genomes Project Phase 3 reference panel (1000Genomes Project Consortium, 2015. ...
Background: We recently developed a multi-ancestry polygenic risk score (PRS) that effectively stratifies prostate cancer risk across populations. In this study, we validated the performance of the PRS in the multi-ancestry Million Veteran Program (MVP) and additional independent studies.
Methods: Within each ancestry population, the association of PRS with prostate cancer risk was evaluated separately in each case-control study and then combined in a fixed-effects inverse-variance-weighted meta-analysis. We further assessed the effect modification by age and estimated the age-specific absolute risk of prostate cancer for each ancestry population.
Results: The PRS was evaluated in 31,925 cases and 490,507 controls, including men from European (22,049 cases, 414,249 controls), African (8,794 cases, 55,657 controls), and Hispanic (1,082 cases, 20,601 controls) populations. Comparing men in the top decile (90-100% of the PRS) to the average 40-60% PRS category, the prostate cancer odds ratio (OR) was 3.8-fold in European ancestry men (95% CI=3.62-3.96), 2.8-fold in African ancestry men (95% CI=2.59-3.03), and 3.2-fold in Hispanic men (95% CI=2.64-3.92). The PRS did not discriminate risk of aggressive versus non-aggressive prostate cancer. However, the OR diminished with advancing age (European ancestry men in the top decile: ≤55 years, OR=7.11; 55-60 years, OR=4.26; >70 years, OR=2.79). Men in the top PRS decile reached 5% absolute prostate cancer risk ~10 years younger than men in the 40-60% PRS category.
Conclusions: Our findings validate the multi-ancestry PRS as an effective prostate cancer risk stratification tool across populations. A clinical study of PRS is warranted to determine if the PRS could be used for risk-stratified screening and early detection.
Funding: This work was supported by the National Cancer Institute at the National Institutes of Health (grant numbers U19 CA214253 to C.A.H., U01 CA257328 to C.A.H., U19 CA148537 to C.A.H., R01 CA165862 to C.A.H., K99 CA246063 to B.F.D, and T32CA229110 to F.C), the Prostate Cancer Foundation (grants 21YOUN11 to B.F.D. and 20CHAS03 to C.A.H.), the Achievement Rewards for College Scientists Foundation Los Angeles Founder Chapter to B.F.D, and the Million Veteran Program-MVP017. This research has been conducted using the UK Biobank Resource under application number 42195. This research is based on data from the Million Veteran Program, Office of Research and Development, and the Veterans Health Administration. This publication does not represent the views of the Department of Veteran Affairs or the United States Government.
... 3 Genetic factors play an important role in prostate cancer susceptibility (2,3) and racial/ethnic 4 disparities in disease incidence (3). We recently developed a multi-ancestry polygenic risk score 5 (PRS) that effectively stratifies prostate cancer risk across populations (3). The PRS could 6 potentially be an effective tool to identify men across diverse populations at higher risk of 7 developing prostate cancer and allow them to make more informed decisions regarding at what 8 age(s) and how frequently to undergo PSA screening. ...
... The MADCaP Network dataset included 405 prostate cancer cases and 396 controls from sub-Saharan Africa, as previously described (5,15), with a substantial proportion of cases diagnosed at late stages. The MADCaP samples were genotyped on a customized array designed to capture common genetic variation in diverse African populations, and genotyping and quality control have been described in detail elsewhere (5). ...
... The MADCaP Network dataset included 405 prostate cancer cases and 396 controls from sub-Saharan Africa, as previously described (5,15), with a substantial proportion of cases diagnosed at late stages. The MADCaP samples were genotyped on a customized array designed to capture common genetic variation in diverse African populations, and genotyping and quality control have been described in detail elsewhere (5). GWAS data were imputed using the 1000 Genomes Project Phase 3 reference panel (13). ...
Background: We recently developed a multi-ancestry polygenic risk score (PRS) that effectively stratifies prostate cancer risk across populations. In this study, we validated the performance of the PRS in the multi-ancestry Million Veteran Program (MVP) and additional independent studies.
Methods: Within each ancestry population, the association of PRS with prostate cancer risk was evaluated separately in each case-control study and then combined in a fixed-effects inverse-variance-weighted meta-analysis. We further assessed the effect modification by age and estimated the age-specific absolute risk of prostate cancer for each ancestry population.
Results: The PRS was evaluated in 31,925 cases and 490,507 controls, including men from European (22,049 cases, 414,249 controls), African (8,794 cases, 55,657 controls), and Hispanic (1,082 cases, 20,601 controls) populations. Comparing men in the top decile (90-100% of the PRS) to the average 40-60% PRS category, the prostate cancer OR was increased 3.8-fold in European ancestry men (95% CI=3.62-3.96), 2.8-fold in African ancestry men (95% CI=2.59-3.03), and 3.2-fold in Hispanic men (95% CI=2.64-3.92). The PRS did not discriminate risk of aggressive versus non-aggressive prostate cancer. However, the OR diminished with advancing age (European ancestry men in the top decile: ≤55 years, OR=7.11; 55-60 years, OR=4.26; >70 years, OR=2.79). Men in the top PRS decile reached 5% absolute prostate cancer risk ~10 years younger than men in the 40-60% PRS category.
Conclusions: Our findings validate the multi-ancestry PRS as an effective prostate cancer risk stratification tool across populations. A clinical study of PRS is warranted to determine if the PRS could be used for risk-stratified screening and early detection.
Funding: This work was supported by the National Cancer Institute at the National Institutes of Health (grant numbers U19 CA214253 to C.A.H., U01 CA257328 to C.A.H., U19 CA148537 to C.A.H., R01 CA165862 to C.A.H., K99 CA246063 to B.F.D, and T32CA229110 to F.C), the Prostate Cancer Foundation (grants 21YOUN11 to B.F.D. and 20CHAS03 to C.A.H.), the Achievement Rewards for College Scientists Foundation Los Angeles Founder Chapter to B.F.D, and the Million Veteran Program-MVP017. This research has been conducted using the UK Biobank Resource under application number 42195. This research is based on data from the Million Veteran Program, Office of Research and Development, and the Veterans Health Administration. This publication does not represent the views of the Department of Veteran Affairs or the United States Government.
... For 2 additional studies, dual analyses were performed on genomics platforms in Africa and the USA. 56,57 There has been an increased acknowledgement of population-based disparities in cancer research, unequal distribution of biomedical funding and the shortcomings of not including more diverse populations in genomics research. 10,39,70,75 To this end, the American Association for Cancer Research (AACR), the American Cancer Society (ACS), the American Society of Clinical Oncology (ASCO) and the National Cancer Institute (NCI) released a position statement with comprehensive recommendations to address these disparities, including reforms to address biomedical research funding for developing and under-resourced countries. ...
... Twelve studies included biosamples from Ghana, 29,31-34,51-57 ; however, 7 of the 12 studies used the same set of biobanked biosamples, 29,31-33,51,52,55 and 2 studies 34,53 used genotype data derived from the biobanked biosamples. Only 3 other studies54,56,57 presented analyses of newly collected Ghanaian biosamples. Similarly, the Uganda-linked studies all used biosamples and/or data derived from the same set of biosamples.32,34,53,58,59 ...
Prostate cancer disproportionately affects men of African descent and it is estimated that Africa will bear the highest disease burden in the next decade. Underlying genomic factors may contribute to prostate cancer disparities; however, it is unclear whether Africa has prioritised genomics research toward addressing these disparities. A Pubmed review was performed of publications spanning a 15-year period, with specific focus on prostate cancer genomics research that included samples from Africa and investigators in Africa. Data are presented on research publications from Africa relative to similar publications from different geographical regions, and more specifically, the extent of disparities and the contributions to prostate cancer knowledge as a result of genomics research that included African samples and African institutions. Limited publication output may reflect the infrastructure and funding challenges in Africa. Widespread cooperation should be fostered by sharing capacity and leveraging existing expertise to address the growing cancer burden facing the continent.
... The loci enriched with GS ≥ 8 and PSA ≥ 20 ng/ml, 22q13.2 and 2p11.2, have shown evidence of transferability among different population groups [40][41][42][43]. The pattern of PCa risk allele identification from GWAS is typical of a recent report by the MadCap Network that there are significant individual and population-level differences in PCa risk within the Africa population [44]. Among men of African ancestry, Haiman et al. [45] identified novel risk variants on 17q21 (rs7210100; odds ratio per allele= 1.51; p=3.4×10 −13 ), which has approximately 5% penetrance among AA compared with 1% in the white race. ...
... The impact of this is that most of the GWAS Consortium are largely focused on potential ancestors of AA, excluding largely the Northern, Middle, and other parts of African countries unexplored [61,62]. There are significant individual and population-level differences in prostate cancer risk such that the inclusion of a new set of the population will result in a new ancestry-specific signal [44]. Currently, the GWAS approach identified common, low-penetrance, and shared PCa predisposing variants among the African population. ...
Background
Prostate cancer (PCa) has one of the highest heritability of all major cancers, where the genetic contribution has been documented, and knowledge about the molecular genetics of the disease is increasing. However, the extent and aspects to which genetic variants explain PCa heritability in Africa are limited.
Main body
In this review, we summarize studies that highlight how identified genetic variants explain differences in PCa incidence and presentation across ethnic groups. We also present the knowledge gaps in PCa genetics in Africa and why Africa represents an untapped potential ground for genetic studies on PCa. A significant number of genome-wide association studies, linkage, and fine-mapping analyses have been conducted globally, and that explains 30–33% of PCa heritability. The African ancestry has a significant mention in PCa incidence and presentation. To date, the candidate gene approach has replicated 23 polymorphisms including dinucleotide and trinucleotide repeats in 16 genes. CYP17-rs743572 , CYP3A4-rs2740574 , CYP3A5-rs776746 , CYP3A43-rs501275 , and haplotype blocks, containing these variants, are significantly associated with PCa among some population groups but not others. With the few existing studies, the extent of genetic diversity in Africa suggests that genetic associations of PCa to African ancestry go beyond nucleotide sequence polymorphisms, to a level of environmental adaptation, which may interpret genetic risk profiles. Also, the shreds of evidence suggest that evolutionary history contributes to the high rates of PCa relative to African ancestry, and genetic associations do not always replicate across populations.
Conclusion
The genetic architecture of PCa in Africa provides important contributions to the global understanding of PCa specifically the African-ancestry hypothesis. There is a need for more prostate cancer consortiums to justify the heritable certainties of PCa among Africans, and emphasis should be placed on the genetic epidemiological model of PCa in Africa.
... Attempts are now being made to evaluate genetic susceptibly using polygenic risk scores (PRS) for cancer in the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network. Over and above the H3Africa array, this network has designed a genotyping array to aid the identification of Afrocentric variants for cancer and to explore polygenic risk scores [34]. An earlier study of a genetic risk score containing 100 European derived genetic variants found that the top 10% of Ugandan men had a 4.86-fold (95%CI:2.70, ...
... 8.76) increase in prostate cancer risk [35]. However, through the evidence from the MADCaP network, the heterogeneity of PRS prediction within continental Africans was depicted [34], implying findings from Uganda may not be applied to other African countries. Thus, more efforts are required to evaluate the possible heterogeneity of PRS prediction within the continent. ...
Non-communicable diseases (NCDs) kill more than 41 million people every year, accounting for 71% of all deaths globally. The prevalence of NCDs is estimated to be higher than that of infectious diseases in Africa by 2030. Precision medicine may help with early identification of cases, resulting in timely prevention and improvement in the efficacy of treatments. However, Africa has been lagging behind in genetic research, a key component of the precision medicine initiative. A number of genomic research initiatives which could lead to translational genomics are emerging on the African continent which includes the Non-communicable Diseases Genetic Heritage Study (NCDGHS) and the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network. These offer a promise that precision medicine can be applied in African countries. This review evaluates the advances of genetic studies for cancer, hypertension, type 2 diabetes and body mass index (BMI) in Africa.
... Beyond their prognostic importance in Black men, mutations in DNA damage repair pathways might alternatively confer sensitivity to platinum-based chemotherapy and targeted therapies such as poly(ADP-ribose) polymerase (PARP) inhibitors [50][51][52][53][54][55][56][57] . Use of novel genotyping arrays (such as the MADCaP array) have facilitated identification of prostate cancer-associated loci and the generation of polygenic risk scores (PRS) for stratification of genetic risk for prostate cancer across African populations 58 . PRS in Black men and white men based on public genomic datasets have also been compared, showing considerable differences, supportive of a racial disparity in prostate cancer occurrence 59,60 . ...
Black men with prostate cancer have historically had worse outcomes than white men with prostate cancer. The causes of this disparity in outcomes are multi-factorial, but a potential basis is that prostate cancers in Black men are biologically distinct from prostate cancers in white men. Evidence suggests that genetic and ancestral factors, molecular pathways involving androgen and non-androgen receptor signalling, inflammation, epigenetics, the tumour microenvironment and tumour metabolism are contributing factors to the racial disparities observed. Key genetic and molecular pathways linked to prostate cancer risk and aggressiveness have potential clinical relevance. Describing biological drivers of prostate cancer disparities could inform efforts to improve outcomes for Black men with prostate cancer.
... MADCaP is a consortium of epidemiologic studies addressing the high prostate cancer burden in African ancestry men. 47,48 Multiethnic Cohort (MEC). MEC is a prospective cohort study that enrolled >215,000 Hawaii/Los Angeles residents ages 45-75 years between 1993-1996. ...
We conducted a multi-ancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry; 58,236 African ancestry; 23,546 Hispanic/Latino; 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (p≤5e-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n=95,768). Meta-analyzing discovery and replication (n=392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our new polygenic risk score reached 16.9% (95% CI=16.1%-17.8%) in European ancestry, 9.5% (95% CI=7.0%-12.2%) in African ancestry, 18.6% (95% CI=15.8%-21.4%) in Hispanic/Latino, and 15.3% (95% CI=12.7%-18.1%) in Asian ancestry, and lower for higher age. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, with potential to personalize prostate cancer screening.
... 33 MADCaP samples were genotyped using a novel genotyping array optimized for ne-mapping and detecting cancer associations in sub-Saharan Africa. 34 An additional 835 cases and 667 controls from the Uganda Prostate Cancer Study (UGPCS) 30 were included, as were 623 cases and 620 controls from the Ghana Prostate Cancer Study. 32 While no exclusion criteria were applied based on disease severity, 35% of cases analyzed that were diagnosed with aggressive forms of CaP (Gleason score ≥ 8). ...
Men of African descent have the highest prostate cancer (CaP) incidence and mortality rates, yet the genetic basis of CaP in African men has been understudied. We used genomic data from 3,963 CaP cases and 3,509 controls recruited in Ghana, Nigeria, Senegal, South Africa, and Uganda, to infer ancestry-specific genetic architectures and fine-mapped disease associations. Fifteen independent associations at 8q24.21, 6q22.1, and 11q13.3 reached genome-wide significance, including four novel associations. Intriguingly, multiple lead SNPs are private alleles, a pattern arising from recent mutations and the out-of-Africa bottleneck. These African-specific alleles contribute to haplotypes with odds ratios above 2.4. We found that the genetic architecture of CaP differs across Africa, with effect size differences contributing more to this heterogeneity than allele frequency differences. Population genetic analyses reveal that African CaP associations are largely governed by neutral evolution. Collectively, our findings emphasize the utility of conducting genetic studies that use diverse populations.
... We also constructed a PRS using the African ancestry-specific effects estimated from African ancestry men (10 367 cases and 10 986 controls) [1]. The PRS association with PCa risk was assessed in six studies included in the GWASs (''discovery sample'') and evaluated for replication in an independent sample from the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network (''replication sample''; Supplementary Table 3) [20,21]. ...
Background:
Genetic factors play an important role in prostate cancer (PCa) susceptibility.
Objective:
To discover common genetic variants contributing to the risk of PCa in men of African ancestry.
Design, setting, and participants:
We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry.
Outcome measurements and statistical analysis:
Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness.
Results and limitations:
Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4).
Conclusions:
This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry.
Patient summary:
In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.
... In general, autosomal dominant cases are more likely to be seen in younger adults and present familial clustering, whereas autosomal recessive cases and X-linked cases are sporadic with an older age of onset [15,16]. To date, there have been numerous studies of biomarkers for primary and metastatic PCA based on single-and multi-omics, with both shared salient genetic characteristics [17] and differences across the ethnic groups [18,19]. Moreover, genetic heterogeneity was also seen at multiple levels including age [20], Gleason ...
Since 1978, with the first IVF (in vitro fertilization) baby birth in Manchester (England), more than eight million IVF babies have been born throughout the world, and many new techniques and discoveries have emerged in reproductive medicine. To summarize the modern technology and progress in reproductive medicine, all scientific papers related to reproductive medicine, especially papers related to reproductive translational medicine, were fully searched, manually curated and reviewed. Results indicated whether male reproductive medicine or female reproductive medicine all have made significant progress, and their markers have experienced the progress from karyotype analysis to single-cell omics. However, due to the lack of comprehensive databases, especially databases collecting risk exposures, disease markers and models, prevention drugs and effective treatment methods, the application of the latest precision medicine technologies and methods in reproductive medicine is limited.
... The HOXB13 X285K variant adds to growing evidence of regional differences in Africa for prostate cancer risk variants [8,9] and provides the first evidence of a genetic factor that is limited to specific African ancestry populations, although studies in other populations are needed to better understand the distribution of this variant in Africa. This investigation also demonstrates the importance and necessity of building diverse reference panels to facilitate the discovery of rare ancestry-specific risk variants and the need for larger sequencing studies in prostate cancer. ...
A rare African ancestry–specific germline deletion variant in HOXB13 (X285K, rs77179853) was recently reported in Martinican men with early-onset prostate cancer. Given the role of HOXB13 germline variation in prostate cancer, we investigated the association between HOXB13 X285K and prostate cancer risk in a large sample of 22 361 African ancestry men, including 11 688 prostate cancer cases. The risk allele was present only in men of West African ancestry, with an allele frequency in men that ranged from 0.40% in Ghana and 0.31% in Nigeria to 0% in Uganda and South Africa, with a range of frequencies in men with admixed African ancestry from North America and Europe (0–0.26%). HOXB13 X285K was associated with 2.4-fold increased odds of prostate cancer (95% confidence interval [CI] = 1.5-3.9, p = 2 × 10⁻⁴), with greater risk observed for more aggressive and advanced disease (Gleason ≥8: odds ratio [OR] = 4.7, 95% CI = 2.3–9.5, p = 2 × 10⁻⁵; stage T3/T4: OR = 4.5, 95% CI = 2.0–10.0, p = 2 × 10⁻⁴; metastatic disease: OR = 5.1, 95% CI = 1.9–13.7, p = 0.001). We estimated that the allele arose in West Africa 1500–4600 yr ago. Further analysis is needed to understand how the HOXB13 X285K variant impacts the HOXB13 protein and function in the prostate. Understanding who carries this mutation may inform prostate cancer screening in men of West African ancestry.
Patient summary
A rare African ancestry–specific germline deletion in HOXB13, found only in men of West African ancestry, was reported to be associated with an increased risk of overall and advanced prostate cancer. Understanding who carries this mutation may help inform screening for prostate cancer in men of West African ancestry.
... Previous studies have indicated that this is a reasonable PBS threshold. [57][58][59] To correct for the effects of linkage disequilibrium (LD), we selected the eQTL with the top PBS score in each 100 kb genomic window. To increase rigor, analyses were repeated using a cutoff of the top 0.1% eQTL PBS scores (also LD pruned). ...
Large numbers of expression quantitative trait loci (eQTLs) have recently been identified in humans, and many of these regulatory variants have large allele frequency differences between populations. Here, we conducted genome-wide scans of selection to identify adaptive eQTLs (i.e., eQTLs with large population branch statistics). We then tested whether tissue pleiotropy affects whether eQTLs are more or less likely to be adaptive and identified tissues that have been key targets of positive selection during the last 100,000 years. Top adaptive eQTL outliers include rs1043809, rs66899053, and rs2814778 (a SNP that is associated with malaria resistance). We found that effect sizes of eQTLs were negatively correlated with population branch statistics, and that adaptive eQTLs affect two-thirds as many tissues as non-adaptive eQTLs. Because the tissue breadth of an eQTL can be viewed as a measure of pleiotropy, these results imply that pleiotropy inhibits adaptation. The proportion of eQTLs that are adaptive varies by tissue, and we found that eQTLs that regulate expression in testis, thyroid, blood, or sun-exposed skin are enriched for signatures of positive selection. By contrast, eQTLs that regulate expression in the cerebrum or female-specific tissues have a relative lack of adaptive outliers. Scans of selection also reveal that many adaptive eQTLs are closely linked to disease-associated loci. Taken together, our results indicate that eQTLs have played an important role in recent human evolution.
... An unsupervised 104 principal component analysis (PCA) and heatmaps with dendrograms were performed on all analyzed samples based 105 on the fraction of ten infiltrating immune cells as determined by QuanTIseq. The analysis was based on the methods 106 reported by Vichi et al. and Granato et al. [19,20]. Principal Component Analysis (PCA) was visualized through the 107 built-in R functions prcomp().and ...
Immunotherapy has changed the standard of treatment for many cancers. However, the same treatments showed disappointing outcomes in cervical cancer so far. Thus, understanding the mechanisms that support the immune tolerance of cervical cancer will provide a way to design new strategies to enhance immunotherapies. Here, we characterized cellular compositions of the immune infiltrates in cervical cancer and investigated if the tumor immune landscape is a predictor for patient prognosis. The fraction of ten immune infiltrates of cervical and other cancers were analyzed by using QuanTIseq software base on the bulk mRNA sequencing data from The Cancer Genome Atlas Program (TCGA). Cervical cancer is one of the cancers that had the lowest percentage of total immune infiltrates, but it had the highest ratio for CD8 T cells to all immune infiltrates among all solid cancers. Both the principal components (PCA) analysis and heatmap with dendrogram analysis showed that cervical cancer had a similar immune infiltrated microenvironment with other squamous cell carcinomas, such as head and neck cancer and lung squamous cell cancer. The PCA and heatmap with dendrogram analysis showed that cervical cancer and HPV positive head and neck cancers were clustered more closer and partially separated with HPV negative head and neck cancer. Further analysis showed that HPV-positive cervical and head and neck cancers had a significantly higher level of CD8 T cells and M1-liked macrophages, but a lower level of M2 macrophages. The survival analysis showed that a higher level of CD8 T cells was associated with a better patient prognosis. However, immuno-suppressive immune infiltrates including M2 macrophages and Treg cells that are known to suppress anti-tumor immunity also demonstrated positive patient overall survival. Our study provided a conceptual framework to understand the tumor immune microenvironment of cervical cancer. Our results also demonstrated that the immune infiltrates can be a prognosis marker for cervical cancer.
Simple Summary
Cervical cancer is the most common gynecologic cancer and the fourth leading cause of cancer-related death in women worldwide. There are relatively limited treatment options for late-stage cervical cancer. Immunotherapy is a new therapeutic treatment developed with great success in treating many cancers, but the same treatment has not been producing satisfactory results in many cases of cervical cancer. In the present study, we provided a comprehensive immune characterization specifically for cervical cancer. We determined the prognostic value of a specific subtype of tumor-infiltrating immune cells for clinical outcomes and demonstrated that HPV infection affected the immune cell infiltration and induce pro-inflammatory phenotypes. Our study provides a systematic insight into the tumor immune microenvironment of cervical cancers and offers a conceptual framework for the future design of rational combination treatment strategies to improve immunotherapy outcomes.
... Several international efforts are also trying to identify ethnic-specific risk SNPs and assess generally the utility of the polygenic risk scores currently in use [3,25]. These will help guide the development of a cross-ethnic PCa screening programme in diverse populations [26][27][28]. ...
Objectives
To assess the feasibility and uptake of a community‐based prostate cancer (PCa) screening programme selecting men according to their genetic risk of PCa. To assess the uptake of PCa screening investigations by men invited for screening. The uptake of the pilot study would guide the opening of the larger BARCODE1 study recruiting 5000 men.
Subjects and Methods
Healthy males aged 55–69 years were invited to participate via their general practitioners (GPs). Saliva samples were collected via mailed collection kits. After DNA extraction, genotyping was conducted using a study specific assay. Genetic risk was based on genotyping 130 germline PCa risk single nucleotide polymorphisms (SNPs). A polygenic risk score (PRS) was calculated for each participant using the sum of weighted alleles for 130 SNPs. Study participants with a PRS lying above the 90th centile value were invited for PCa screening by prostate magnetic resonance imaging (MRI) and biopsy.
Results
Invitation letters were sent to 1434 men. The overall study uptake was 26% (375/1436) and 87% of responders were eligible for study entry. DNA genotyping data were available for 297 men and 25 were invited for screening. After exclusions due to medical comorbidity/invitations declined, 18 of 25 men (72%) underwent MRI and biopsy of the prostate. There were seven diagnoses of PCa (38.9%). All cancers were low‐risk and were managed with active surveillance.
Conclusion
The BARCODE1 Pilot has shown this community study in the UK to be feasible, with an overall uptake of 26%. The main BARCODE1 study is now open and will recruit 5000 men. The results of BARCODE1 will be important in defining the role of genetic profiling in targeted PCa population screening.
Patient Summary
What is the paper about?
Very few prostate cancer screening programmes currently exist anywhere in the world. Our pilot study investigated if men in the UK would find it acceptable to have a genetic test based on a saliva sample to examine their risk of prostate cancer development. This test would guide whether men are offered prostate cancer screening tests.
What does it mean for patients?
We found that the study design was acceptable: 26% of men invited to take part agreed to have the test. The majority of men who were found to have an increased genetic risk of prostate cancer underwent further tests offered (prostate MRI scan and biopsy). We have now expanded the study to enrol 5000 men. The BARCODE1 study will be important in examining whether this approach could be used for large‐scale population prostate cancer screening.
... Strengthening our core laboratory generated value by establishing stronger partnerships across disciplines and repurposing otherwise latent infrastructure and human resource capacity. The collective experiences from past transnational collaborations by the authors [3][4][5][6][7][8], culminated in the vision to establish the COVID19 laboratory and its unprecedented execution in two weeks. The laboratory is now an accredited The pre-existing mechanisms for coordination of initiatives, communication and fundraising already in place at the College of Medicine was another critical element for success. ...
The novel COVID-19 pandemic prompted an unprecedented Institutional reaction to aggregate existing capacity from silos of research laboratories to establish a multidisciplinary research laboratory for COVID19 testing. In less than two weeks, resources were mobilized from the community to strengthen public health response and epidemic control. Such strengthening of institutional research capacity to support public health response contributes to a natural knowledge transfer, facilitates collaboration, and generates new frontiers for knowledge production that should ultimately lead to professional development and retention of skilled human resources. This report describes the pre-established mechanisms and involvement of the authors that made it possible to set-up a multidisciplinary laboratory in a remarkably short period of time. We also discuss the opportunities and sustainability of multidisciplinary laboratory research post-COVID19. Existing institutional capacity can be repurposed to establish multidisciplinary research laboratories to support the strengthening of basic and clinical translational research capacity in resource limited settings and impact on public health and scientific knowledge for socioeconomic development.
African ancestry is a significant risk factor for prostate cancer and advanced disease. Yet, genetic studies have largely been conducted outside the context of Sub-Saharan Africa, identifying 278 common risk variants contributing to a multiethnic polygenic risk score, with rare variants focused on a panel of roughly 20 pathogenic genes. Based on this knowledge, we were unable to determine polygenic risk or differentiate prostate cancer status interrogating whole genome data for 113 Black South African men. To further assess for potentially functional common and rare variant associations, we interrogated 247,780 exomic variants for 798 Black South African men using a case versus control or aggressive versus non-aggressive study design. Notable genes of interest included HCP5 , RFX6 and H3C1 for risk, and MKI67 and KLF5 for aggressive disease. Our study highlights the need for further inclusion across the African diaspora to establish African-relevant risk models aimed at reducing prostate cancer health disparities.
Background: Ancestry is often viewed as a more objective and less objectionable population descriptor than race or ethnicity. Perhaps reflecting this, usage of the term “ancestry” is rapidly growing in genetics research, with ancestry groups referenced in many situations. The appropriate usage of population descriptors in genetics research is an ongoing source of debate. Sound normative guidance should rest on an empirical understanding of current usage; in the case of ancestry, questions about how researchers use the concept, and what they mean by it, remain unanswered.
Methods: Systematic literature analysis of 205 articles at least tangentially related to human health from diverse disciplines that use the concept of ancestry, and semi-structured interviews with 44 lead authors of some of those articles.
Results: Ancestry is relied on to structure research questions and key methodological approaches. Yet researchers struggle to define it, and/or offer diverse definitions. For some ancestry is a genetic concept, but for many—including geneticists—ancestry is only tangentially related to genetics. For some interviewees, ancestry is explicitly equated to ethnicity; for others it is explicitly distanced from it. Ancestry is operationalized using multiple data types (including genetic variation and self-reported identities), though for a large fraction of articles (26%) it is impossible to tell which data types were used. Across the literature and interviews there is no consistent understanding of how ancestry relates to genetic concepts (including genetic ancestry and population structure), nor how these genetic concepts relate to each other. Beyond this conceptual confusion, practices related to summarizing patterns of genetic variation often rest on uninterrogated conventions. Continental labels are by far the most common type of label applied to ancestry groups. We observed many instances of slippage between reference to ancestry groups and racial groups.
Conclusion: Ancestry is in practice a highly ambiguous concept, and far from an objective counterpart to race or ethnicity. It is not uniquely a “biological” construct, and it does not represent a “safe haven” for researchers seeking to avoid evoking race or ethnicity in their work. Distinguishing genetic ancestry from ancestry more broadly will be a necessary part of providing conceptual clarity.
Background
The rarity and heterogeneity of pediatric cancers make it difficult to assess risk factors associated with the development of cancer in this group. This also determines the quantity and quality of evidence for etiological factors linked to pediatric cancers. Evidence on the risk factors associated with pediatric cancers is scarce; however, it has been accumulating slowly over the years. As the disease burden shifts from communicable to non-communicable diseases, most of these low- to middle-income countries (LMICs) find themselves overburdened with changing health care priorities and needs. In sub-Saharan Africa, it is of major importance to pay particular attention to risk factors associated with pediatric cancer.
Objective
To map evidence on risk factors associated with pediatric cancers in sub-Saharan Africa (SSA).
Methods
This review was guided by Arksey and O’Malley’s framework for conducting scoping reviews. Four electronic databases were searched in December 2018, and another manual search was conducted in February 2022 to include newly published eligible articles. The databases searched included PubMed and Health Source: Nursing/Academic Edition. We also searched articles from an academic search engine, Google scholar. This review included articles reporting the relevant outcomes of this study and articles reporting cancers in children in the 0–15 years age range. This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews (PRISMA-ScR): checklist and explanation.
Results
We retrieved 7391 articles from the initial database. The final number of studies that were included for data extraction was 15. Evidence from the retrieved studies suggests that most childhood cancers in the SSA region are infection-induced. The type of cancer mostly reported is Burkitt Lymphoma and is diagnosed mostly in the tropical region of SSA. The type of risk factors was divided into three types: infection-induced, genetic, and demographic risk factors. Overall, based on the articles retrieved, there was limited evidence on the risk factors associated with pediatric cancers in SSA.
Conclusion
The limited evidence on the risk factors coupled with the lack of evidence on the true burden of these malignancies in the SSA hampers efforts to set priorities for childhood cancer control. Formulation of effective preventative (where possible) measures and treatment regimens will need proper assessment of risk factors.
Human cell lines (CLs) are key assets for biomedicine but lack ancestral diversity. Here, we explore why genetic diversity among cell-based models is essential for making preclinical research more equitable and widely translatable. We lay out practical actions that can be taken to improve inclusivity in study design.
PurposeTumor infiltration by immunosuppressive myeloid cells or tumor-associated macrophages (TAMs) contributes to tumor progression and metastasis. In contrast to their adult counterparts, higher TAM signatures do not correlate with aggressive tumor behavior in pediatric brain tumors. While prominent TAM infiltrates exist before and after radiation, the degree to which irradiated macrophages and microglia support progression or leptomeningeal metastasis remains unclear. Patients with medulloblastoma often present with distant metastases and tumor recurrence is largely incurable, making them prime candidates for the study of novel approaches to prevent neuroaxis dissemination and recurrence.Methods
Macrophage depletion was achieved using CSF-1 receptor inhibitors (CSF-1Ri), BLZ945 and AFS98, with or without whole brain radiation in a variety of medulloblastoma models, including patient-derived xenografts bearing Group 3 medulloblastoma and a transgenic Sonic Hedgehog (Ptch1+/−, Trp53−/−) medulloblastoma model.ResultsEffective reduction of microglia, TAM, and spinal cord macrophage with CSF-1Ri resulted in negligible effects on the rate of local and spinal recurrences or survival following radiation. Results were comparable between medulloblastoma subgroups. While notably few tumor-infiltrating lymphocytes (TILs) were detected, average numbers of CD3+ TILs and FoxP3+ Tregs did not differ between groups following treatment and tumor aggressiveness by Ki67 proliferation index was unaltered.Conclusion
In the absence of other microenvironmental influences, medulloblastoma-educated macrophages do not operate as tumor-supportive cells or promote leptomeningeal recurrence in these models. Our data add to a growing body of literature describing a distinct immunophenotype amid the medulloblastoma microenvironment and highlight the importance of appropriate pediatric modeling prior to clinical translation.
SHP2 is a ubiquitous tyrosine phosphatase involved in regulating both tumor and immune cell signaling. In this study, we discovered a novel immune modulatory function of SHP2. Targeting this protein with allosteric SHP2 inhibitors promoted anti-tumor immunity, including enhancing T cell cytotoxic function and immune-mediated tumor regression. Knockout of SHP2 using CRISPR/Cas9 gene editing showed that targeting SHP2 in cancer cells contributes to this immune response. Inhibition of SHP2 activity augmented tumor intrinsic IFNγ signaling resulting in enhanced chemoattractant cytokine release and cytotoxic T cell recruitment, as well as increased expression of MHC Class I and PD-L1 on the cancer cell surface. Furthermore, SHP2 inhibition diminished the differentiation and inhibitory function of immune suppressive myeloid cells in the tumor microenvironment. SHP2 inhibition enhanced responses to anti-PD-1 blockade in syngeneic mouse models. Overall, our study reveals novel functions of SHP2 in tumor immunity and proposes that targeting SHP2 is a promising strategy for cancer immunotherapy.
Developments in genomics in the last decade has improved our understanding of the role of genetics in health and disease. One area where the impact of genomics is very noticeable is in oncology, specifically in terms of diagnosis and elucidating genetic predisposition to rare and common cancers. Sub-Saharan Africa (SSA) stands to benefit from cancer genomics, given recent spikes in the incidence of various types of cancers in the region. This mini review presents, from a health and science equity perspective, how genomics could shape cancer research and clinical care in SSA. We highlight some pan-African genomics and cancer initiatives that are facilitating cancer genomics research in SSA. We conclude with recommendations on how the ideals of equity may be advanced in cancer genomics initiatives in SSA.
Backgrounds:
Genetic diversity is greatest within Africa, in particular the KhoeSan click-speaking peoples of southern Africa. South African populations represent admixture fractions including differing degrees of African, African-KhoeSan and non-African genetic ancestries. Within the United States, African ancestry has been linked to prostate cancer presentation and mortality. Together with environmental contributions, genetics is a significant risk factor for high-risk prostate cancer, defined by a pathological Gleason score ≥ 8.
Methods:
Using genotype array data merged with ancestry informative reference data, we investigate the contribution of African ancestral fractions to high-risk prostate cancer. Our study includes 152 South African men of African (Black) or African-admixed (Coloured) ancestries, in which 40% showed high-risk prostate cancer.
Results:
Genetic fractions were determined for averaging an equal African to non-African genetic ancestral contribution in the Coloured; we found African ancestry to be linked to high-risk prostate cancer (P-value = 0.0477). Adjusting for age, the associated African ancestral fraction was driven by a significant KhoeSan over Bantu contribution, defined by Gleason score ≥ 8 (P-value = 0.02329) or prostate specific antigen levels ≥20 ng/ml (P-value = 0.03713). Additionally, we observed the mean overall KhoeSan contribution to be increased in Black patients with high-risk (11.8%) over low-risk (10.9%) disease. Linking for the first time KhoeSan ancestry to a common modern disease, namely high-risk prostate cancer, we tested in this small study the validity of using KhoeSan ancestry as a surrogate for identifying potential high-risk prostate cancer risk loci. As such, we identified four loci within chromosomal regions 2p11.2, 3p14, 8q23 and 22q13.2 (P-value = all age-adjusted < 0.01), two of which have previously been associated with high-risk prostate cancer.
Conclusions:
Our study suggests that ancient KhoeSan ancestry may be linked to common modern diseases, specifically those of late onset and therefore unlikely to have undergone exclusive selective pressure. As such we show within a uniquely admixed South African population a link between KhoeSan ancestry and high-risk prostate cancer, which may explain the 2-fold increase in presentation in Black South Africans compared with African Americans.
Polygenic risk scores (PRS) are poised to improve biomedical outcomes via precision medicine. However, the major ethical and scientific challenge surrounding clinical implementation of PRS is that those available today are several times more accurate in individuals of European ancestry than other ancestries. This disparity is an inescapable consequence of Eurocentric biases in genome-wide association studies, thus highlighting that—unlike clinical biomarkers and prescription drugs, which may individually work better in some populations but do not ubiquitously perform far better in European populations—clinical uses of PRS today would systematically afford greater improvement for European-descent populations. Early diversifying efforts show promise in leveling this vast imbalance, even when non-European sample sizes are considerably smaller than the largest studies to date. To realize the full and equitable potential of PRS, greater diversity must be prioritized in genetic studies, and summary statistics must be publically disseminated to ensure that health disparities are not increased for those individuals already most underserved. This Perspective discusses scientific and ethical considerations regarding the clinical use of polygenic risk scores, highlighting the pressing need to diversify cohorts for genetic studies beyond European-ancestry populations.
Background
Accurate assessment of health disparities requires unbiased knowledge of genetic risks in different populations. Unfortunately, most genome-wide association studies use genotyping arrays and European samples. Here, we integrate whole genome sequence data from global populations, results from thousands of genome-wide association studies (GWAS), and extensive computer simulations to identify how genetic disease risks can be misestimated.
Results
In contrast to null expectations, we find that risk allele frequencies at known disease loci are significantly different for African populations compared to other continents. Strikingly, ancestral risk alleles are found at 9.51% higher frequency in Africa, and derived risk alleles are found at 5.40% lower frequency in Africa. By simulating GWAS with different study populations, we find that non-African cohorts yield disease associations that have biased allele frequencies and that African cohorts yield disease associations that are relatively free of bias. We also find empirical evidence that genotyping arrays and SNP ascertainment bias contribute to continental differences in risk allele frequencies. Because of these causes, polygenic risk scores can be grossly misestimated for individuals of African descent. Importantly, continental differences in risk allele frequencies are only moderately reduced if GWAS use whole genome sequences and hundreds of thousands of cases and controls. Finally, comparisons between uncorrected and corrected genetic risk scores reveal the benefits of considering whether risk alleles are ancestral or derived.
Conclusions
Our results imply that caution must be taken when extrapolating GWAS results from one population to predict disease risks in another population.
Electronic supplementary material
The online version of this article (10.1186/s13059-018-1561-7) contains supplementary material, which is available to authorized users.
Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa 1 .
Purpose:
Cancer of the prostate (CaP) is the leading cancer among men in sub-Saharan Africa (SSA). A substantial proportion of these men with CaP are diagnosed at late (usually incurable) stages, yet little is known about the etiology of CaP in SSA.
Methods:
We established the Men of African Descent and Carcinoma of the Prostate Network, which includes seven SSA centers partnering with five US centers to study the genetics and epidemiology of CaP in SSA. We developed common data elements and instruments, regulatory infrastructure, and biosample collection, processing, and shipping protocols. We tested this infrastructure by collecting epidemiologic, medical record, and genomic data from a total of 311 patients with CaP and 218 matched controls recruited at the seven SSA centers. We extracted genomic DNA from whole blood, buffy coat, or buccal swabs from 265 participants and shipped it to the Center for Inherited Disease Research (Baltimore, MD) and the Centre for Proteomics and Genomics Research (Cape Town, South Africa), where genotypes were generated using the UK Biobank Axiom Array.
Results:
We used common instruments for data collection and entered data into the shared database. Double-entered data from pilot participants showed a 95% to 98% concordance rate, suggesting that data can be collected, entered, and stored with a high degree of accuracy. Genotypes were obtained from 95% of tested DNA samples (100% from blood-derived DNA samples) with high concordance across laboratories.
Conclusion:
We provide approaches that can produce high-quality epidemiologic and genomic data in multicenter studies of cancer in SSA.
Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African
genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement
and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents
dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa.
Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture
across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and
hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing
genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in
sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy,
strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient
genotype array design capturing common genetic variation in Africa
Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa 1 .
Precision medicine is being enabled in high-income countries by the growing availability of health data, increasing knowledge of the genetic determinants of disease and variation in response to treatment (pharmacogenomics), and the decreasing costs of data generation, which promote routine application of genomic technologies in the health sector. However, there is uncertainty about the feasibility of applying precision medicine approaches in low- and middle-income countries, due to the lack of population-specific knowledge, skills, and resources. The Human Heredity and Health in Africa (H3Africa) initiative was established to drive new research into the genetic and environmental basis for human diseases of relevance to Africans as well as to build capacity for genomic research on the continent. Precision medicine requires this capacity, in addition to reference data on local populations, and skills to analyze and interpret genomic data from the bedside. The H3Africa consortium is collectively processing samples and data for over 70,000 participants across the continent, accompanied in most cases by rich clinical information on a variety of non-communicable and infectious diseases. These projects are increasingly providing novel insights into the genetic basis of diseases in indigenous populations, insights that have the potential to drive the development of new diagnostics and treatments. The consortium has also invested significant resources into establishing high-quality biorepositories in Africa, a bioinformatic network, and a strong training program that has developed skills in genomic data analysis and interpretation among bioinformaticians, wet-lab researchers, and health-care professionals. Here, we describe the current perspectives of the H3Africa consortium and how it can contribute to making precision medicine in Africa a reality.
Background:
Few studies have evaluated the performance of existing breast cancer risk prediction models among women of African ancestry. In replication studies of genetic variants, a change in direction of the risk association is a common phenomenon. Termed flip-flop, it means that a variant is risk factor in one population but protective in another, affecting the performance of risk prediction models.
Methods:
We used data from the genome-wide association study (GWAS) of breast cancer in the African diaspora (The Root consortium), which included 3686 participants of African ancestry from Nigeria, USA, and Barbados. Polygenic risk scores (PRSs) were constructed from the published odds ratios (ORs) of four sets of susceptibility loci for breast cancer. Discrimination capacity was measured using the area under the receiver operating characteristic curve (AUC).
Results:
Flip-flop phenomenon was observed among 30~40% of variants across studies. Using the 34 variants with consistent directionality among previous studies, we constructed a PRS with AUC of 0.531 (95% confidence interval [CI]: 0.512-0.550), which is similar to the PRS using 93 variants and ORs from European ancestry populations (AUC = 0.525, 95% CI: 0.506-0.544). Additionally, we found the 34-variant PRS has good discriminative accuracy in women with family history of breast cancer (AUC = 0.586, 95% CI: 0.532-0.640).
Conclusions:
We found that PRS based on variants identified from prior GWASs conducted in women of European and Asian ancestries did not provide a comparable degree of risk stratification for women of African ancestry. Further large-scale fine-mapping studies in African ancestry populations are desirable to discover population-specific genetic risk variants.
Ancient DNA pushes human emergence back
Anatomically modern humans evolved in Africa, but pinpointing when has been difficult. Schlebusch et al. sequenced three ancient African genomes from the Stone Age, about 2000 years old, and four from the Iron Age, 300 to 500 years old. One of the oldest samples, sequenced to 13× coverage, appears most closely to resemble individuals from the present-day San population. However, this individual seems to have lacked genetic contributions from other modern African populations, including pastoralists and farmers, which were observed in modern San individuals. Thus, the earliest divergence between human populations may have occurred 350,000 to 260,000 years ago.
Science , this issue p. 652
Background:
Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits.
Methods:
The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background.
Results:
The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis.
Conclusions:
Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures.
Impact:
Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR.
The NHGRI-EBI GWAS Catalog has provided data from published genome-wide association studies since 2008. In 2015, the database was redesigned and relocated to EMBL-EBI. The new infrastructure includes a new graphical user interface (www.ebi.ac.uk/gwas/), ontology supported search functionality and an improved curation interface. These developments have improved the data release frequency by increasing automation of curation and providing scaling improvements. The range of available Catalog data has also been extended with structured ancestry and recruitment information added for all studies. The infrastructure improvements also support scaling for larger arrays, exome and sequencing studies, allowing the Catalog to adapt to the needs of evolving study design, genotyping technologies and user needs in the future.
An analysis by Alice B. Popejoy and Stephanie M. Fullerton indicates that some populations are still being left behind on the road to precision medicine.
The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
Background:
In the UK, a man's lifetime risk of being diagnosed with prostate cancer is 1 in 8. We calculated both the lifetime risk of being diagnosed with and dying from prostate cancer by major ethnic group.
Methods:
Public Health England provided prostate cancer incidence and mortality data for England (2008-2010) by major ethnic group. Ethnicity and mortality data were incomplete, requiring various assumptions and adjustments before lifetime risk was calculated using DevCan (percent, range).
Results:
The lifetime risk of being diagnosed with prostate cancer is approximately 1 in 8 (13.3 %, 13.2-15.0 %) for White men, 1 in 4 (29.3 %, 23.5-37.2 %) for Black men, and 1 in 13 (7.9 %, 6.3-10.5 %) for Asian men, whereas that of dying from prostate cancer is approximately 1 in 24 (4.2 %, 4.2-4.7 %) for White men, 1 in 12 (8.7 %, 7.6-10.6 %) for Black men, and 1 in 44 (2.3 %, 1.9-3.0 %) for Asian men.
Conclusions:
In England, Black men are at twice the risk of being diagnosed with, and dying from, prostate cancer compared to White men. This is an important message to communicate to Black men. White, Black, and Asian men with a prostate cancer diagnosis are all as likely to die from the disease, independent of their ethnicity. Nonetheless, proportionally more Black men are dying from prostate cancer in England.
This tutorial is a learning resource that outlines the basic process and provides specific software tools for implementing a complete genome-wide association analysis. Approaches to post-analytic visualization and interrogation of potentially novel findings are also presented. Applications are illustrated using the free and open-source R statistical computing and graphics software environment, Bioconductor software for bioinformatics and the UCSC Genome Browser. Complete genome-wide association data on 1401 individuals across 861,473 typed single nucleotide polymorphisms from the PennCATH study of coronary artery disease are used for illustration. All data and code, as well as additional instructional resources, are publicly available through the Open Resources in Statistical Genomics project: http://www.stat-gen.org. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
Public perception and anxiety of familial cancer have increased demands for clinical counseling, which may be well equipped for gene testing but less prepared for counseling of the large domain of familial cancer with unknown genetic background. The aim of the present study was to highlight the full scope of familial cancer and the variable levels of risk that need to be considered. Data on the 25 most common cancers were obtained from the Swedish Family Cancer Database and a Poisson regression model was applied to estimate relative risks (RR) distinguishing between family histories of single or multiple affected first-degree relatives and their diagnostic ages. For all cancers, individual risks were significantly increased if a parent or a sibling had a concordant cancer. While the RRs were around 2.00 for most cancers, risks were up to 10-fold increased for some cancers. Familial risks were even higher when multiple relatives were affected. Although familial risks were highest at ages below 60 years, most familial cases were diagnosed at older ages. The results emphasized the value of a detailed family history as a readily available tool for individualized counseling and its preventive potential for a large domain of non-syndromatic familial cancers.
Genome-wide association studies (GWAS) have implicated single nucleotide polymorphisms (SNPs) on chromosomes 2p15, 6q25, 7p15.2, 7q21, 8q24, 10q11, 10q26, 11q13, 17q12, 17q24, 19q13, and Xp11, with prostate cancer (PCa) susceptibility and/or tumour aggressiveness, in populations of African, European, and Asian ancestry. The objective of this study was to confirm these associations in South African Mixed Ancestry and White men. We evaluated 17 prioritised GWAS SNPs in South African cases (331 Mixed Ancestry and 155 White) and controls (178 Mixed Ancestry and 145 White). The replicated SNP associations for the different South African ethnic groups were rs7008482 (8q24) (í µí± = 2.45 × 10 −5), rs6983267 (8q24) (í µí± = 4.48 × 10 −7), and rs10993994 (10q11) (í µí± = 1.40 × 10 −3) in Mixed Ancestry men and rs10993994 (í µí± = 1.56 × 10 −9) in White men. No significant associations were observed for the analyses stratified by disease aggressiveness in the individual and the combined population group analysis. The present study demonstrates that a number of known PCa susceptibility variants may contribute to disease susceptibility in South African men. Larger genetic investigations extended to other South African population groups are warranted to confirm the role of these and other SNPs in disease susceptibility.
Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative
traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across
43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We
describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression
quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association
studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences
of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.
Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.
Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of >10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10(-8); 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.
The majority of sub-Saharan Africans today speak a number of closely related languages collectively referred to as ‘Bantu’ languages. The current distribution of Bantu-speaking populations has been found to largely be a consequence of the movement of people rather than a diffusion of language alone. Linguistic and single marker genetic studies have generated various hypotheses regarding the timing and the routes of the Bantu expansion, but these hypotheses have not been thoroughly investigated. In this study, we re-analysed microsatellite markers typed for large number of African populations that—owing to their fast mutation rates—capture signatures of recent population history. We confirm the spread of west African people across most of sub-Saharan Africa and estimated the expansion of Bantu-speaking groups, using a Bayesian approach, to around 5600 years ago. We tested four different divergence models for Bantu-speaking populations with a distribution comprising three geographical regions in Africa. We found that the most likely model for the movement of the eastern branch of Bantu-speakers involves migration of Bantu-speaking groups to the east followed by migration to the south. This model, however, is only marginally more likely than other models, which might indicate direct movement from the west and/or significant gene flow with the western Branch of Bantu-speakers. Our study use multi-loci genetic data to explicitly investigate the timing and mode of the Bantu expansion and it demonstrates that west African groups rapidly expanded both in numbers and over a large geographical area, affirming the fact that the Bantu expansion was one of the most dramatic demographic events in human history.
Age-adjusted mortality rates for prostate cancer are higher for African-American men compared with those of European ancestry. Recent data suggest that West African men also have elevated risk for prostate cancer relative to European men. Genetic susceptibility to prostate cancer could account for part of this difference. We conducted a genome-wide association study (GWAS) of prostate cancer in West African men in the Ghana Prostate Study. Association testing was performed using multivariable logistic regression adjusted for age and genetic ancestry for 474 prostate cancer cases and 458 population-based controls on the Illumina HumanOmni-5 Quad BeadChip. The most promising association was at 10p14 within an intron of a long non-coding RNA (lncRNA RP11-543F8.2) 360 kb centromeric of GATA3 (p = 1.29E-7). In sub-analyses, SNPs at 5q31.3 were associated with high Gleason score (≥7) cancers, the strongest of which was a missense SNP in PCDHA1 (rs34575154, p = 3.66E-8), and SNPs at Xq28 (rs985081, p = 8.66E-9) and 6q21 (rs2185710, p = 5.95E-8) were associated with low Gleason score (<7) cancers. We sought to validate our findings in silico in the African Ancestry Prostate Cancer GWAS Consortium, but only one SNP, at 10p14, replicated at p < 0.05. Of the 90 prostate cancer loci reported from studies of men of European, Asian or African-American ancestry, we were able to test 81 in the Ghana Prostate Study, and 10 of these replicated at p < 0.05. Further genetic studies of prostate cancer in West African men are needed to confirm our promising susceptibility loci.
Genotype imputation is a statistical technique that is often used to increase the power and resolution of genetic association studies. Imputation methods work by using haplotype patterns in a reference panel to predict unobserved genotypes in a study dataset, and a number of approaches have been proposed for choosing subsets of reference haplotypes that will maximize accuracy in a given study population. These panel selection strategies become harder to apply and interpret as sequencing efforts like the 1000 Genomes Project produce larger and more diverse reference sets, which led us to develop an alternative framework. Our approach is built around a new approximation that uses local sequence similarity to choose a custom reference panel for each study haplotype in each region of the genome. This approximation makes it computationally efficient to use all available reference haplotypes, which allows us to bypass the panel selection step and to improve accuracy at low-frequency variants by capturing unexpected allele sharing among populations. Using data from HapMap 3, we show that our framework produces accurate results in a wide range of human populations. We also use data from the Malaria Genetic Epidemiology Network (MalariaGEN) to provide recommendations for imputation-based studies in Africa. We demonstrate that our approximation improves efficiency in large, sequence-based reference panels, and we discuss general computational strategies for modern reference datasets. Genome-wide association studies will soon be able to harness the power of thousands of reference genomes, and our work provides a practical way for investigators to use this rich information. New methodology from this study is implemented in the IMPUTE2 software package.
Lung adenocarcinoma is the most common histological type of lung cancer, and its incidence is increasing worldwide. To identify genetic factors influencing risk of lung adenocarcinoma, we conducted a genome-wide association study and two validation studies in the Japanese population comprising a total of 6,029 individuals with lung adenocarcinoma (cases) and 13,535 controls. We confirmed two previously reported risk loci, 5p15.33 (rs2853677, P(combined) = 2.8 × 10(-40), odds ratio (OR) = 1.41) and 3q28 (rs10937405, P(combined) = 6.9 × 10(-17), OR = 1.25), and identified two new susceptibility loci, 17q24.3 (rs7216064, P(combined) = 7.4 × 10(-11), OR = 1.20) and 6p21.3 (rs3817963, P(combined) = 2.7 × 10(-10), OR = 1.18). These data provide further evidence supporting a role for genetic susceptibility in the development of lung adenocarcinoma.
The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses – the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferroni-type procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. We conducted a multi-stage genome-wide association study for PrCa and previously reported the results of the first two stages, which identified 16 PrCa susceptibility loci. We report here the results of stage 3, in which we evaluated 1,536 SNPs in 4,574 individuals with prostate cancer (cases) and 4,164 controls. We followed up ten new association signals through genotyping in 51,311 samples in 30 studies from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. In addition to replicating previously reported loci, we identified seven new prostate cancer susceptibility loci on chromosomes 2p11, 3q23, 3q26, 5p12, 6p21, 12q13 and Xq12 (P = 4.0 × 10(-8) to P = 2.7 × 10(-24)). We also identified a SNP in TERT more strongly associated with PrCa than that previously reported. More than 40 PrCa susceptibility loci, explaining ∼25% of the familial risk in this disease, have now been identified.
In search of common risk alleles for prostate cancer that could contribute to high rates of the disease in men of African ancestry, we conducted a genome-wide association study, with 1,047,986 SNP markers examined in 3,425 African-Americans with prostate cancer (cases) and 3,290 African-American male controls. We followed up the most significant 17 new associations from stage 1 in 1,844 cases and 3,269 controls of African ancestry. We identified a new risk variant on chromosome 17q21 (rs7210100, odds ratio per allele = 1.51, P = 3.4 × 10(-13)). The frequency of the risk allele is ∼5% in men of African descent, whereas it is rare in other populations (<1%). Further studies are needed to investigate the biological contribution of this allele to prostate cancer risk. These findings emphasize the importance of conducting genome-wide association studies in diverse populations.
Residents of the Tibetan Plateau show heritable adaptations to extreme altitude. We sequenced 50 exomes of ethnic Tibetans,
encompassing coding sequences of 92% of human genes, with an average coverage of 18× per individual. Genes showing population-specific
allele frequency changes, which represent strong candidates for altitude adaptation, were identified. The strongest signal
of natural selection came from endothelial Per-Arnt-Sim (PAS) domain protein 1 (EPAS1), a transcription factor involved in response to hypoxia. One single-nucleotide polymorphism (SNP) at EPAS1 shows a 78% frequency difference between Tibetan and Han samples, representing the fastest allele frequency change observed
at any human gene to date. This SNP’s association with erythrocyte abundance supports the role of EPAS1 in adaptation to hypoxia. Thus, a population genomic survey has revealed a functionally important locus in genetic adaptation
to high altitude.
We conducted a genome-wide association study on 969 bladder cancer cases and 957 controls from Texas. For fast-track validation, we evaluated 60 SNPs in three additional US populations and validated the top SNP in nine European populations. A missense variant (rs2294008) in the PSCA gene showed consistent association with bladder cancer in US and European populations. Combining all subjects (6,667 cases, 39,590 controls), the overall P-value was 2.14 x 10(-10) and the allelic odds ratio was 1.15 (95% confidence interval 1.10-1.20). rs2294008 alters the start codon and is predicted to cause truncation of nine amino acids from the N-terminal signal sequence of the primary PSCA translation product. In vitro reporter gene assay showed that the variant allele significantly reduced promoter activity. Resequencing of the PSCA genomic region showed that rs2294008 is the only common missense SNP in PSCA. Our data identify rs2294008 as a new bladder cancer susceptibility locus.
Population stratification has long been recognized as a confounding factor in genetic association studies. Estimated ancestries, derived from multi-locus genotype data, can be used to perform a statistical correction for population stratification. One popular technique for estimation of ancestry is the model-based approach embodied by the widely applied program structure. Another approach, implemented in the program EIGENSTRAT, relies on Principal Component Analysis rather than model-based estimation and does not directly deliver admixture fractions. EIGENSTRAT has gained in popularity in part owing to its remarkable speed in comparison to structure. We present a new algorithm and a program, ADMIXTURE, for model-based estimation of ancestry in unrelated individuals. ADMIXTURE adopts the likelihood model embedded in structure. However, ADMIXTURE runs considerably faster, solving problems in minutes that take structure hours. In many of our experiments, we have found that ADMIXTURE is almost as fast as EIGENSTRAT. The runtime improvements of ADMIXTURE rely on a fast block relaxation scheme using sequential quadratic programming for block updates, coupled with a novel quasi-Newton acceleration of convergence. Our algorithm also runs faster and with greater accuracy than the implementation of an Expectation-Maximization (EM) algorithm incorporated in the program FRAPPE. Our simulations show that ADMIXTURE's maximum likelihood estimates of the underlying admixture coefficients and ancestral allele frequencies are as accurate as structure's Bayesian estimates. On real-world data sets, ADMIXTURE's estimates are directly comparable to those from structure and EIGENSTRAT. Taken together, our results show that ADMIXTURE's computational speed opens up the possibility of using a much larger set of markers in model-based ancestry estimation and that its estimates are suitable for use in correcting for population stratification in association studies.
(Cell 177, 26–31; March 21, 2019) Our Commentary described the underrepresentation of individuals of diverse ancestries in genomic studies published to date and the negative consequences of this lack of ethnic diversity on genetic research and genomic medicine. We have identified an error in the Commentary. In the originally published version, the sentence reading “The subjects were of Puerto Rican, Mexican, and African ancestry, populations known to present both the highest asthma prevalence and mortality and the lowest albuterol BDR” is incorrect with respect to the prevalence of asthma in Mexican American populations. This sentence has been revised to read “The subjects were Americans of Mexican, Puerto Rican, and African ancestry; the latter two populations present both the highest asthma prevalence and mortality and the lowest albuterol BDR. Mexican Americans have amongst the lowest prevalence of asthma in the United States.” The authors apologize for any confusion this error may have caused.
The majority of studies of genetic association with disease have been performed in Europeans. This European bias has important implications for risk prediction of diseases across global populations. In this commentary, we justify the need to study more diverse populations using both empirical examples and theoretical reasoning.
The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses — the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.
This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high‐quality cancer registry data, the basis for planning and implementing evidence‐based cancer control programs, are not available in most low‐ and middle‐income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1‐31. © 2018 American Cancer Society
Prostate cancer incidence and mortality rates in African and African American men are greatly elevated compared with other ethnicities. This disparity is likely explained by a combination of social, environmental, and genetic factors. A large number of susceptibility loci have been reported by genome-wide association studies (GWAS), but the contribution of these loci to prostate cancer disparities is unclear. Here, we investigated the population structure of 68 previously reported GWAS loci and calculated genetic disparity contribution statistics to identify SNPs that contribute the most to differences in prostate cancer risk across populations. By integrating GWAS results with allele frequency data, we generated genetic risk scores for 45 African and 19 non-African populations. Tests of natural selection were used to assess why some SNPs have large allele frequency differences across populations. We report that genetic predictions of prostate cancer risks are highest for West African men and lowest for East Asian men. These differences may be explained by the out-of-Africa bottleneck and natural selection. A small number of loci appear to drive elevated prostate cancer risks in men of African descent, including rs9623117, rs6983267, rs10896449, rs10993994, and rs817826. Although most prostate cancer–associated loci are evolving neutrally, there are multiple instances where alleles have hitchhiked to high frequencies with linked adaptive alleles. For example, a protective allele at 2q37 appears to have risen to high frequency in Europe due to selection acting on pigmentation. Our results suggest that evolutionary history contributes to the high rates of prostate cancer in African and African American men.
Significance: A small number of genetic variants cause an elevated risk of prostate cancer in men of West African descent. Cancer Res; 78(9); 2432–43. ©2018 AACR.
Background:
Men of African-ancestry have elevated prostate cancer (PCa) incidence and mortality compared to men of other racial groups. There is support for a genetic contribution to this disparity, with evidence of genetic heterogeneity in the underlying risk alleles between populations. Studies of PCa among African men may inform the contribution of genetic risk factors to the elevated disease burden in this population.
Methods:
We conducted an association study of >100 previously reported PCa risk alleles among 571 incidence cases and 485 controls among Uganda men. Unconditional logistic regression was used to test genetic associations and a polygenic risk score (PRS) was derived to assess the cumulative effect of the known risk alleles in association with PCa risk. In an exploratory analysis, we also tested associations of 17 125 421 genotyped and imputed markers genome-wide in association with PCa risk.
Results:
Of the 111 known risk loci with a frequency >1%, 75 (68%) had effects that were directionally consistent with the initial discovery population,14 (13%) of which were nominally significantly associated with PCa risk at P < 0.05. Compared to men with average risk (25th -75th percentile in PRS distribution), Ugandan men in the top 10% of the PRS, constructed of alleles outside of 8q24, had a 2.9-fold (95%CI: 1.75, 4.97) risk of developing PCa; risk for the top 10% increased to 4.86 (95%CI: 2.70, 8.76) with the inclusion of risk alleles at 8q24. In genome-wide association testing, the strongest associations were noted with known risk alleles located in the 8q24 region, including rs72725854 (OR = 3.37, P = 2.14 × 10-11 ) that is limited to populations of African ancestry (6% frequency).
Conclusions:
The ∼100 known PCa risk variants were shown to effectively stratify PCa risk in Ugandan men, with 10% of men having a >4-fold increase in risk. The 8q24 risk region was also found to be a major contributor to PCa risk in Ugandan men, with the African ancestry-specific risk variant rs72725854 estimated to account for 12% of PCa in this population.
Recent studies have highlighted the imperatives of including diverse and under-represented individuals in human genomics research and the striking gaps in attaining that inclusion. With its multidecade experience in supporting research and policy efforts in human genomics, the National Human Genome Research Institute is committed to establishing foundational approaches to study the role of genomic variation in health and disease that include diverse populations. Large-scale efforts to understand biology and health have yielded key scientific findings, lessons and recommendations on how to increase diversity in genomic research studies and the genomic research workforce. Increased attention to diversity will increase the accuracy, utility and acceptability of using genomic information for clinical care.
The genomes of ancient humans, Neandertals, and Denisovans contain many alleles that influence disease risks. Using genotypes at 3,180 disease-associated loci, we estimated the disease burden of 147 ancient genomes. After correcting for missing data, genetic risk scores (GRS) were generated for nine disease categories and the set of all combined diseases. We used these genetic risk scores to examine the effects of different types of subsistence, geography, and sample age on the number of risk alleles in each ancient genome. On a broad scale, hereditary disease risks are similar for ancient hominins and modern-day humans, and the GRS percentiles of ancient individuals span the full range of what is observed in present-day individuals. In addition, there is evidence that ancient pastoralists may have had healthier genomes than hunter-gatherers and agriculturalists. We also observed a temporal trend whereby genomes from the recent past are more likely to be healthier than genomes from the deep past. This calls into question the idea that modern lifestyles have caused genetic load to increase over time. Focusing on individual genomes, we found that the overall genomic health of the Altai Neandertal is worse than 97% of present-day humans and that Ötzi, the Tyrolean Iceman, had a genetic predisposition for gastrointestinal and cardiovascular diseases. As demonstrated by this work, ancient genomes afford us new opportunities to diagnose past human health, which has previously been limited by the quality and completeness of remains.
The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.
Prostate cancer rates vary substantially by race, ethnicity, and geography. These disparities can be explained by variation in access to screening and treatment, variation in exposure to prostate cancer risk factors, and variation in the underlying biology of prostate carcinogenesis (including genomic propensity of some groups to develop biologically aggressive disease). It is clear that access to screening and access to treatment are critical influencing factors of prostate cancer rates; yet, even among geographically diverse populations with similar access to care (eg, low- and medium-income countries), African descent men have higher prostate cancer rates and poorer prognosis. To date, the proportion of prostate cancer that can be explained by environmental exposures is small, and the effect of these factors across different racial, ethnic, or geographical populations is poorly understood. In contrast, prostate cancer has one of the highest heritabilities of all major cancers. Numerous genetic susceptibility markers have been identified from family-based studies, candidate gene association studies, and genome-wide association studies. Some prostate cancer loci, including the risk loci found at chromosome 8q24, have consistent effects in all groups studied to date. However, replication of many susceptibility loci across race, ethnicity, and geography remains limited, and additional studies in certain populations (particularly in men of African descent) are needed to better understand the underlying genetic basis of prostate cancer.
Prostate cancer (PCa) is the most common non-skin cancer men in developed countries. Despite years of research, no strong modifiable risk factor for PCa has been found. The two most significant cancer risk factors, smoking and obesity, do not appear to be strong risk factors for PCa. A recent systematic review and meta-analysis summarized the current literature of tobacco use and PCa mortality and incidence (1). This meta-analysis included 51 cohort studies (50,349 incident cases and 4,082,606 cohort participants) and found a dichotomized association between smoking and PCa risk. Current smoking was associated with an increased risk of PCa [rate ratio (RR): 1.06; 95% confidence interval (CI), 0.98–1.15] in studies completed in 1995 or earlier [before the prostate-specific antigen (PSA) screening era], and a reduced risk of PCa (RR: 0.84, 95% CI, 0.79–0.89) in studies completed afterward (after the wide spread of PSA screening).
Assessing linkage disequilibrium (LD) across ancestral populations is a powerful approach for investigating population-specific genetic structure as well as functionally mapping regions of disease susceptibility. Here we present LDlink, a web-based collection of bioinformatic modules that query single nucleotide polymorphisms (SNPs) in population groups of interest to generate haplotype tables and interactive plots. Modules are designed with an emphasis on ease of use, query flexibility, and interactive visualization of results. Phase 3 haplotype data from the 1000 Genomes Project are referenced for calculating pairwise metrics of LD, searching for proxies in high LD, and enumerating all observed haplotypes. LDlink is tailored for investigators interested in mapping common and uncommon disease susceptibility loci by focusing on output linking correlated alleles and highlighting putative functional variants.
LDlink is a free and publically available web tool which can be accessed at http://analysistools.nci.nih.gov/LDlink/.
Published by Oxford University Press 2015. This work is written by US Government employees and are in the public domain in the US.
Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.
Whole genome sequencing and SNP genotyping arrays can paint strikingly different pictures of demographic history and natural selection. This is because genotyping arrays contain biased sets of pre-ascertained SNPs. In this short review, we use comparisons between high-coverage whole genome sequences of African hunter-gatherers and data from genotyping arrays to highlight how SNP ascertainment bias distorts population genetic inferences. Sample sizes and the populations in which SNPs are discovered affect the characteristics of observed variants. We find that SNPs on genotyping arrays tend to be older and present in multiple populations. In addition, genotyping arrays cause allele frequency distributions to be shifted towards intermediate frequency alleles, and estimates of linkage disequilibrium are modified. Since population genetic analyses depend on allele frequencies, it is imperative that researchers are aware of the effects of SNP ascertainment bias. With this in mind, we describe multiple ways to correct for SNP ascertainment bias.
Long-range migrations and the resulting admixtures between populations have been important forces shaping human genetic diversity. Most existing methods for detecting and reconstructing historical admixture events are based on allele frequency divergences or patterns of ancestry segments in chromosomes of admixed individuals. An emerging new approach harnesses the exponential decay of admixture-induced linkage disequilibrium (LD) as a function of genetic distance. Here, we comprehensively develop LD-based inference into a versatile tool for investigating admixture. We present a new weighted LD statistic that can be used to infer mixture proportions as well as dates with fewer constraints on reference populations than previous methods. We define an LD-based three-population test for admixture and identify scenarios in which it can detect admixture events that previous formal tests cannot. We further show that we can uncover phylogenetic relationships among populations by comparing weighted LD curves obtained using a suite of references. Finally, we describe several improvements to the computation and fitting of weighted LD curves that greatly increase the robustness and speed of the calculations. We implement all of these advances in a software package, ALDER, which we validate in simulations and apply to test for admixture among all populations from the Human Genome Diversity Project (HGDP), highlighting insights into the admixture history of Central African Pygmies, Sardinians, and Japanese.
Multiple genetic studies have confirmed associations of 8q24 variants with susceptibility to prostate cancer (CaP). However, the magnitude of risk conferred in men living in West Africa is unknown.
Here we determine the prevalence of 8q24 risk alleles and test for association with CaP risk alleles in West African (WA) descent populations from rural Nigeria, Cameroon, and the Caribbean island of Jamaica. Ten 8q24 SNPs were genotyped in histologically confirmed CaP cases (n = 308) and clinically evaluated controls (n = 469). In addition, unrelated individuals from Sierra Leone (n = 380) were genotyped for comparison of allele frequency comparisons.
SNPs rs6983561, rs7008482, and rs16901979 were significantly associated with CaP risk in WAs (P < 0.03). No associations with CaP were observed in our Caribbean samples. Risk alleles for rs6983267, rs7008482, and rs7000448 were highly prevalent (>84%) in West Africa. We also reveal that the A-risk allele for the 'African-specific' SNP bd11934905 was not observed in 1,886 chromosomes from three WA ethnic groups suggesting that this allele may not be common across West Africa, but is geographically restricted to specific ethnic group(s).
We provide evidence of association of 8q24 SNPs with prostate cancer risk in men from Nigeria and Cameroon. Our study is the first to reveal genetic risk due to 8q24 variants (in particular, region 2) with CaP within two WA countries. Most importantly, in light of the disparate burden of CaP in African-Americans, our findings support the need for larger genetic studies in WA descent populations to validate and discern function of susceptibility loci in the 8q24 region.
Wide variation exists internationally for prostate cancer (PCa) rates due to differences in detection practices, treatment, and lifestyle and genetic factors.
We present contemporary variations in PCa incidence and mortality patterns across five continents using the most recent data from the International Agency for Research on Cancer.
PCa incidence and mortality estimates for 2008 from GLOBOCAN are presented. We also examine recent trends in PCa incidence rates for 40 countries and mortality rates for 53 countries from 1985 and onward via join-point analyses using an augmented version of Cancer Incidence in Five Continents and the World Health Organization mortality database.
Estimated PCa incidence rates remain most elevated in the highest resource counties worldwide including North America, Oceania, and western and northern Europe. Mortality rates tend to be higher in less developed regions of the world including parts of South America, the Caribbean, and sub-Saharan Africa. Increasing PCa incidence rates during the most recent decade were observed in 32 of the 40 countries examined, whereas trends tended to stabilize in 8 countries. In contrast, PCa mortality rates decreased in 27 of the 53 countries under study, whereas rates increased in 16 and remained stable in 10 countries.
PCa incidence rates increased in nearly all countries considered in this analysis except in a few high-income countries. In contrast, the increase in PCa mortality rates mainly occurred in lower resource settings, with declines largely confined to high-resource countries.