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Opi DH, Ndila CM, Uyoga S, Macharia AW, Fennell C, Ochola LB, Nyutu G, Siddondo BR, Ojal J, Shebe M, Awuondo KO, Mturi N, Peshu N, Tsofa B, Band G, Maitland K, Kwiatkowski DP, Rockett KA, Williams TN, Rowe JA. Non-O ABO blood group genotypes differ in their associations with Plasmodium falciparum rosetting and severe malaria. PLoS Genet 2023; 19:e1010910. [PMID: 37708213 PMCID: PMC10522014 DOI: 10.1371/journal.pgen.1010910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 09/26/2023] [Accepted: 08/08/2023] [Indexed: 09/16/2023] Open
Abstract
Blood group O is associated with protection against severe malaria and reduced size and stability of P. falciparum-host red blood cell (RBC) rosettes compared to non-O blood groups. Whether the non-O blood groups encoded by the specific ABO genotypes AO, BO, AA, BB and AB differ in their associations with severe malaria and rosetting is unknown. The A and B antigens are host RBC receptors for rosetting, hence we hypothesized that the higher levels of A and/or B antigen on RBCs from AA, BB and AB genotypes compared to AO/BO genotypes could lead to larger rosettes, increased microvascular obstruction and higher risk of malaria pathology. We used a case-control study of Kenyan children and in vitro adhesion assays to test the hypothesis that "double dose" non-O genotypes (AA, BB, AB) are associated with increased risk of severe malaria and larger rosettes than "single dose" heterozygotes (AO, BO). In the case-control study, compared to OO, the double dose genotypes consistently had higher odds ratios (OR) for severe malaria than single dose genotypes, with AB (OR 1.93) and AO (OR 1.27) showing most marked difference (p = 0.02, Wald test). In vitro experiments with blood group A-preferring P. falciparum parasites showed that significantly larger rosettes were formed with AA and AB host RBCs compared to OO, whereas AO and BO genotypes rosettes were indistinguishable from OO. Overall, the data show that ABO genotype influences P. falciparum rosetting and support the hypothesis that double dose non-O genotypes confer a greater risk of severe malaria than AO/BO heterozygosity.
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Affiliation(s)
- D. Herbert Opi
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
- Centre for Immunity, Infection and Evolution, Institute of Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Carolyne M. Ndila
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Sophie Uyoga
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Alex W. Macharia
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Clare Fennell
- Centre for Immunity, Infection and Evolution, Institute of Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Lucy B. Ochola
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Gideon Nyutu
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Bethseba R. Siddondo
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - John Ojal
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Mohammed Shebe
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Kennedy O. Awuondo
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Neema Mturi
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Norbert Peshu
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Benjamin Tsofa
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
| | - Gavin Band
- Wellcome Centre for Human Genetics, Oxford, United Kingdom
| | - Kathryn Maitland
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
- Institute for Global Health Innovation, Department of Surgery and Cancer, Imperial College, London, United Kingdom
| | | | | | - Thomas N. Williams
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya
- Institute for Global Health Innovation, Department of Surgery and Cancer, Imperial College, London, United Kingdom
| | - J. Alexandra Rowe
- Centre for Immunity, Infection and Evolution, Institute of Immunology and Infection Research, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
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Akoth M, Odhiambo J, Omolo B. Genome-wide association testing in malaria studies in the presence of overdominance. Malar J 2023; 22:119. [PMID: 37038187 PMCID: PMC10084622 DOI: 10.1186/s12936-023-04533-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 03/15/2023] [Indexed: 04/12/2023] Open
Abstract
BACKGROUND In human genetics, heterozygote advantage (heterosis) has been detected in studies that focused on specific genes but not in genome-wide association studies (GWAS). For example, heterosis is believed to confer resistance to certain strains of malaria in patients heterozygous for the sickle-cell gene, haemoglobin S (HbS). Yet the power of allelic tests can be substantially diminished by heterosis. Since GWAS (and haplotype-associations) also utilize allelic tests, it is unclear to what degree GWAS could underachieve because heterosis is ignored. METHODS In this study, a two-step approach to genetic association testing in malaria studies in a GWAS setting that may enhance the power of the tests was proposed, by identifying the underlying genetic model first before applying the association tests. Generalized linear models for dominant, recessive, additive, and heterotic effects were fitted and model selection was performed. This was achieved via tests of significance using the MAX and allelic tests, noting the minimum p-values across all the models and the proportion of tests that a given genetic model was deemed the best. An example dataset, based on 17 SNPs, from a robust genetic association study and simulated genotype datasets, were used to illustrate the method. Case-control genotype data on malaria from Kenya and Gambia were used for validation. RESULTS AND CONCLUSION Results showed that the allelic test returned some false negatives under the heterosis model, suggesting reduced power in testing genetic association. Disparities were observed for some chromosomes in the Kenyan and Gambian datasets, including the sex chromosomes. Thus, GWAS and haplotype associations should be treated with caution, unless the underlying genetic model had been determined.
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Affiliation(s)
- Morine Akoth
- Strathmore Institute of Mathematical Sciences, Strathmore University, Ole Sangale Road, Nairobi, Kenya.
| | - John Odhiambo
- Strathmore Institute of Mathematical Sciences, Strathmore University, Ole Sangale Road, Nairobi, Kenya
| | - Bernard Omolo
- Strathmore Institute of Mathematical Sciences, Strathmore University, Ole Sangale Road, Nairobi, Kenya
- Division of Mathematics & Computer Science, University of South Carolina-Upstate, 800 University Way, Spartanburg, USA
- School of Public Health, Faculty of Health Science, University of the Witwatersrand, Johannesburg, South Africa
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Thiam A, Nisar S, Adjemout M, Gallardo F, Ka O, Mbengue B, Diop G, Dieye A, Marquet S, Rihet P. ATP2B4 regulatory genetic variants are associated with mild malaria. Malar J 2023; 22:68. [PMID: 36849945 PMCID: PMC9972758 DOI: 10.1186/s12936-023-04503-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 02/18/2023] [Indexed: 03/01/2023] Open
Abstract
BACKGROUND Genome-wide association studies have identified ATP2B4 as a severe malaria resistance gene. Recently, 8 potential causal regulatory variants have been shown to be associated with severe malaria. METHODS Genotyping of rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452 was performed in 154 unrelated individuals (79 controls and 75 mild malaria patients). rs10751450, rs10751451 and rs10751452 were genotyped by Taqman assays, whereas the fragment of the ATP2B4 gene containing the remaining SNPs was sequenced. Logistic regression analysis was used to assess the association between the SNPs and mild malaria. RESULTS The results showed that mild malaria was associated with rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452. The homozygous genotypes for the major alleles were associated with an increased risk of mild malaria. Furthermore, the haplotype containing the major alleles and that containing the minor alleles were the most frequent haplotypes. Individuals with the major haplotypes had a significantly higher risk of mild malaria compared to the carriers of the minor allele haplotype. CONCLUSIONS ATP2B4 polymorphisms that have been associated with severe malaria are also associated with mild malaria.
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Affiliation(s)
- Alassane Thiam
- grid.418508.00000 0001 1956 9596Unité d’Immunogénétique, Institut Pasteur de Dakar, Dakar, Senegal
| | - Samia Nisar
- grid.5399.60000 0001 2176 4817Aix Marseille Univ, INSERM, TAGC, MarMaRa Institute, Marseille, France ,grid.444997.30000 0004 1761 3137Sardar Bahadur Khan Women’s University, Quetta, 1800 Balochistan Pakistan
| | - Mathieu Adjemout
- grid.5399.60000 0001 2176 4817Aix Marseille Univ, INSERM, TAGC, MarMaRa Institute, Marseille, France
| | - Frederic Gallardo
- grid.5399.60000 0001 2176 4817Aix Marseille Univ, INSERM, TAGC, MarMaRa Institute, Marseille, France
| | - Oumar Ka
- grid.8191.10000 0001 2186 9619Service d’Immunologie, Université Cheikh Anta Diop de Dakar, Dakar, Senegal
| | - Babacar Mbengue
- grid.8191.10000 0001 2186 9619Service d’Immunologie, Université Cheikh Anta Diop de Dakar, Dakar, Senegal
| | - Gora Diop
- grid.418508.00000 0001 1956 9596Unité d’Immunogénétique, Institut Pasteur de Dakar, Dakar, Senegal
| | - Alioune Dieye
- grid.8191.10000 0001 2186 9619Service d’Immunologie, Université Cheikh Anta Diop de Dakar, Dakar, Senegal
| | - Sandrine Marquet
- Aix Marseille Univ, INSERM, TAGC, MarMaRa Institute, Marseille, France.
| | - Pascal Rihet
- Aix Marseille Univ, INSERM, TAGC, MarMaRa Institute, Marseille, France.
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Joof F, Hartmann E, Jarvis A, Colley A, Cross JH, Avril M, Prentice AM, Cerami C. Genetic variations in human ATP2B4 gene alter Plasmodium falciparum in vitro growth in RBCs from Gambian adults. Malar J 2023; 22:5. [PMID: 36604655 PMCID: PMC9817369 DOI: 10.1186/s12936-022-04359-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 11/03/2022] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Polymorphisms in ATP2B4 coding for PMCA4b, the primary regulator of erythrocyte calcium concentration, have been shown by GWAS and cross-sectional studies to protect against severe malaria but the mechanism remains unknown. METHODS Using a recall-by-genotype design, we investigated the impact of a common haplotype variant in ATP2B4 using in vitro assays that model erythrocyte stage malaria pathogenesis. Ninety-six donors representing homozygote (carriers of the minor allele, C/C), heterozygote (T/C) and wildtype (T/T) carriers of the tagging SNP rs1541252 were selected from a cohort of over 12,000 participants in the Keneba Biobank. RESULTS Red blood cells (RBCs) from homozygotes showed reduced PMCA4b protein expression (mean fluorescence intensities (MFI = 2428 ± 124, 3544 ± 159 and 4261 ± 283], for homozygotes, heterozygotes and wildtypes respectively, p < 0.0001) and slower rates of calcium expulsion (calcium t½ ± SD = 4.7 ± 0.5, 1.8 ± 0.3 and 1.9 ± 0.4 min, p < 0.0001). Growth of a Plasmodium falciparum laboratory strain (FCR3) and two Gambian field isolates was decreased in RBCs from homozygotes compared to heterozygotes and wildtypes (p < 0.01). Genotype group did not affect parasite adhesion in vitro or var-gene expression in malaria-infected RBCs. Parasite growth was inhibited by a known inhibitor of PMCA4b, aurintricarboxylic acid (IC50 = 122uM CI: 110-134) confirming its sensitivity to calcium channel blockade. CONCLUSION The data support the hypothesis that this ATP2B4 genotype, common in The Gambia and other malaria-endemic areas, protects against severe malaria through the suppression of parasitaemia during an infection. Reduction in parasite density plays a pivotal role in disease outcome by minimizing all aspects of malaria pathogenesis. Follow up studies are needed to further elucidate the mechanism of protection and to determine if this ATP2B4 genotype carries a fitness cost or increases susceptibility to other human disease.
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Affiliation(s)
- Fatou Joof
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Banjul, The Gambia
| | | | | | - Alhassan Colley
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Banjul, The Gambia
| | - James H Cross
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Banjul, The Gambia
| | | | - Andrew M Prentice
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Banjul, The Gambia
| | - Carla Cerami
- Medical Research Council Unit The Gambia at London School of Hygiene and Tropical Medicine, Banjul, The Gambia.
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Risk score prediction model based on single nucleotide polymorphism for predicting malaria: a machine learning approach. BMC Bioinformatics 2022; 23:325. [PMID: 35934714 PMCID: PMC9358850 DOI: 10.1186/s12859-022-04870-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 08/01/2022] [Indexed: 11/25/2022] Open
Abstract
Background The malaria risk prediction is currently limited to using advanced statistical methods, such as time series and cluster analysis on epidemiological data. Nevertheless, machine learning models have been explored to study the complexity of malaria through blood smear images and environmental data. However, to the best of our knowledge, no study analyses the contribution of Single Nucleotide Polymorphisms (SNPs) to malaria using a machine learning model. More specifically, this study aims to quantify an individual's susceptibility to the development of malaria by using risk scores obtained from the cumulative effects of SNPs, known as weighted genetic risk scores (wGRS).
Results We proposed an SNP-based feature extraction algorithm that incorporates the susceptibility information of an individual to malaria to generate the feature set. However, it can become computationally expensive for a machine learning model to learn from many SNPs. Therefore, we reduced the feature set by employing the Logistic Regression and Recursive Feature Elimination (LR-RFE) method to select SNPs that improve the efficacy of our model. Next, we calculated the wGRS of the selected feature set, which is used as the model's target variables. Moreover, to compare the performance of the wGRS-only model, we calculated and evaluated the combination of wGRS with genotype frequency (wGRS + GF). Finally, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), and Ridge regression algorithms are utilized to establish the machine learning models for malaria risk prediction. Conclusions Our proposed approach identified SNP rs334 as the most contributing feature with an importance score of 6.224 compared to the baseline, with an importance score of 1.1314. This is an important result as prior studies have proven that rs334 is a major genetic risk factor for malaria. The analysis and comparison of the three machine learning models demonstrated that LightGBM achieves the highest model performance with a Mean Absolute Error (MAE) score of 0.0373. Furthermore, based on wGRS + GF, all models performed significantly better than wGRS alone, in which LightGBM obtained the best performance (0.0033 MAE score). Supplementary Information The online version contains supplementary material available at 10.1186/s12859-022-04870-0.
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Donta MS, Srivastava Y, McCrea PD. Delta-Catenin as a Modulator of Rho GTPases in Neurons. Front Cell Neurosci 2022; 16:939143. [PMID: 35860313 PMCID: PMC9289679 DOI: 10.3389/fncel.2022.939143] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 06/09/2022] [Indexed: 12/03/2022] Open
Abstract
Small Rho GTPases are molecular switches that are involved in multiple processes including regulation of the actin cytoskeleton. These GTPases are activated (turned on) and inactivated (turned off) through various upstream effector molecules to carry out many cellular functions. One such upstream modulator of small Rho GTPase activity is delta-catenin, which is a protein in the p120-catenin subfamily that is enriched in the central nervous system. Delta-catenin affects small GTPase activity to assist in the developmental formation of dendrites and dendritic spines and to maintain them once they mature. As the dendritic arbor and spine density are crucial for synapse formation and plasticity, delta-catenin's ability to modulate small Rho GTPases is necessary for proper learning and memory. Accordingly, the misregulation of delta-catenin and small Rho GTPases has been implicated in several neurological and non-neurological pathologies. While links between delta-catenin and small Rho GTPases have yet to be studied in many contexts, known associations include some cancers, Alzheimer's disease (AD), Cri-du-chat syndrome, and autism spectrum disorder (ASD). Drawing from established studies and recent discoveries, this review explores how delta-catenin modulates small Rho GTPase activity. Future studies will likely elucidate how PDZ proteins that bind delta-catenin further influence small Rho GTPases, how delta-catenin may affect small GTPase activity at adherens junctions when bound to N-cadherin, mechanisms behind delta-catenin's ability to modulate Rac1 and Cdc42, and delta-catenin's ability to modulate small Rho GTPases in the context of diseases, such as cancer and AD.
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Affiliation(s)
- Maxsam S. Donta
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- Program in Genetics and Epigenetics, The University of Texas MD Anderson Cancer Center University of Texas Health Science Center Houston Graduate School of Biomedical Science, Houston, TX, United States
| | - Yogesh Srivastava
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Pierre D. McCrea
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
- Program in Genetics and Epigenetics, The University of Texas MD Anderson Cancer Center University of Texas Health Science Center Houston Graduate School of Biomedical Science, Houston, TX, United States
- Program in Neuroscience, The University of Texas MD Anderson Cancer Center University of Texas Health Science Center Houston Graduate School of Biomedical Science, Houston, TX, United States
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Identification of ATP2B4 Regulatory Element Containing Functional Genetic Variants Associated with Severe Malaria. Int J Mol Sci 2022; 23:ijms23094849. [PMID: 35563239 PMCID: PMC9101746 DOI: 10.3390/ijms23094849] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 04/15/2022] [Accepted: 04/22/2022] [Indexed: 12/04/2022] Open
Abstract
Genome-wide association studies for severe malaria (SM) have identified 30 genetic variants mostly located in non-coding regions. Here, we aimed to identify potential causal genetic variants located in these loci and demonstrate their functional activity. We systematically investigated the regulatory effect of the SNPs in linkage disequilibrium (LD) with the malaria-associated genetic variants. Annotating and prioritizing genetic variants led to the identification of a regulatory region containing five ATP2B4 SNPs in LD with rs10900585. We found significant associations between SM and rs10900585 and our candidate SNPs (rs11240734, rs1541252, rs1541253, rs1541254, and rs1541255) in a Senegalese population. Then, we demonstrated that both individual SNPs and the combination of SNPs had regulatory effects. Moreover, CRISPR/Cas9-mediated deletion of this region decreased ATP2B4 transcript and protein levels and increased Ca2+ intracellular concentration in the K562 cell line. Our data demonstrate that severe malaria-associated genetic variants alter the expression of ATP2B4 encoding a plasma membrane calcium-transporting ATPase 4 (PMCA4) expressed on red blood cells. Altering the activity of this regulatory element affects the risk of SM, likely through calcium concentration effect on parasitaemia.
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8
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Tai KY, Dhaliwal J, Balasubramaniam V. Leveraging Mann-Whitney U test on large-scale genetic variation data for analysing malaria genetic markers. Malar J 2022; 21:79. [PMID: 35264165 PMCID: PMC8905822 DOI: 10.1186/s12936-022-04104-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 02/24/2022] [Indexed: 11/10/2022] Open
Abstract
Background The malaria risk analysis of multiple populations is crucial and of great importance whilst compressing limitations. However, the exponential growth in diversity and accumulation of genetic variation data obtained from malaria-infected patients through Genome-Wide Association Studies opens up unprecedented opportunities to explore the significant differences between genetic markers (risk factors), particularly in the resistance or susceptibility of populations to malaria risk. Thus, this study proposes using statistical tests to analyse large-scale genetic variation data, comprising 20,854 samples from 11 populations within three continents: Africa, Oceania, and Asia. Methods Even though statistical tests have been utilized to conduct case–control studies since the 1950s to link risk factors to a particular disease, several challenges faced, including the choice of data (ordinal vs. non-ordinal) and test (parametric vs. non-parametric). This study overcomes these challenges by adopting the Mann–Whitney U test to analyse large-scale genetic variation data; to explore the statistical significance of markers between populations; and to further identify the highly differentiated markers. Results The findings of this study revealed a significant difference in the genetic markers between populations (p < 0.01) in all the case groups and most control groups. However, for the highly differentiated genetic markers, a significant difference (p < 0.01) was present for most genetic markers with varying p-values between the populations in the case and control groups. Moreover, several genetic markers were observed to have very significant differences (p < 0.001) across all populations, while others exist between certain specific populations. Also, several genetic markers have no significant differences between populations. Conclusions These findings further support that the genetic markers contribute differently between populations towards malaria resistance or susceptibility, thus showing differences in the likelihood of malaria infection. In addition, this study demonstrated the robustness of the Mann–Whitney U test in analysing genetic markers in large-scale genetic variation data, thereby indicating an alternative method to explore genetic markers in other complex diseases. The findings hold great promise for genetic markers analysis, and the pipeline emphasized in this study can fully be reproduced to analyse new data. Supplementary Information The online version contains supplementary material available at 10.1186/s12936-022-04104-x.
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Affiliation(s)
- Kah Yee Tai
- School of Information Technology, Monash University Malaysia, Subang Jaya, Selangor, Malaysia
| | - Jasbir Dhaliwal
- School of Information Technology, Monash University Malaysia, Subang Jaya, Selangor, Malaysia.
| | - Vinod Balasubramaniam
- Jeffrey Cheah School of Medicine & Health Sciences, Monash University Malaysia, Subang Jaya, Selangor, Malaysia
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Venkataraman GR, DeBoever C, Tanigawa Y, Aguirre M, Ioannidis AG, Mostafavi H, Spencer CCA, Poterba T, Bustamante CD, Daly MJ, Pirinen M, Rivas MA. Bayesian model comparison for rare-variant association studies. Am J Hum Genet 2021; 108:2354-2367. [PMID: 34822764 PMCID: PMC8715195 DOI: 10.1016/j.ajhg.2021.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 11/02/2021] [Indexed: 12/12/2022] Open
Abstract
Whole-genome sequencing studies applied to large populations or biobanks with extensive phenotyping raise new analytic challenges. The need to consider many variants at a locus or group of genes simultaneously and the potential to study many correlated phenotypes with shared genetic architecture provide opportunities for discovery not addressed by the traditional one variant, one phenotype association study. Here, we introduce a Bayesian model comparison approach called MRP (multiple rare variants and phenotypes) for rare-variant association studies that considers correlation, scale, and direction of genetic effects across a group of genetic variants, phenotypes, and studies, requiring only summary statistic data. We apply our method to exome sequencing data (n = 184,698) across 2,019 traits from the UK Biobank, aggregating signals in genes. MRP demonstrates an ability to recover signals such as associations between PCSK9 and LDL cholesterol levels. We additionally find MRP effective in conducting meta-analyses in exome data. Non-biomarker findings include associations between MC1R and red hair color and skin color, IL17RA and monocyte count, and IQGAP2 and mean platelet volume. Finally, we apply MRP in a multi-phenotype setting; after clustering the 35 biomarker phenotypes based on genetic correlation estimates, we find that joint analysis of these phenotypes results in substantial power gains for gene-trait associations, such as in TNFRSF13B in one of the clusters containing diabetes- and lipid-related traits. Overall, we show that the MRP model comparison approach improves upon useful features from widely used meta-analysis approaches for rare-variant association analyses and prioritizes protective modifiers of disease risk.
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Affiliation(s)
| | - Christopher DeBoever
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Yosuke Tanigawa
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Matthew Aguirre
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | | | | | | | - Timothy Poterba
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Carlos D Bustamante
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA; Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Mark J Daly
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland; Department of Mathematics and Statistics, University of Helsinki, Helsinki 00014, Finland.
| | - Manuel A Rivas
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA.
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Ndila CM, Nyirongo V, Macharia AW, Jeffreys AE, Rowlands K, Hubbart C, Busby GBJ, Band G, Harding RM, Rockett KA, Williams TN. Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α 3.7I form of α-thalassaemia using genome-wide microarray data. Wellcome Open Res 2021; 5:287. [PMID: 34632085 PMCID: PMC8474104 DOI: 10.12688/wellcomeopenres.16320.2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/10/2021] [Indexed: 12/26/2022] Open
Abstract
Background: The -α
3.7I-thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations. Methods: In this study, we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR. Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha (
HBA) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results. Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies.
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Affiliation(s)
- Carolyne M Ndila
- Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, PO BOX 230-80108, Kenya
| | - Vysaul Nyirongo
- United Nation Statistics Division, United Nations, New York, New York, 10017, USA
| | - Alexander W Macharia
- Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, PO BOX 230-80108, Kenya
| | - Anna E Jeffreys
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, OX3 7BN, UK
| | - Kate Rowlands
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, OX3 7BN, UK
| | - Christina Hubbart
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, OX3 7BN, UK
| | - George B J Busby
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, OX3 7BN, UK.,Centre for Genomics and Global Health, Big Data Institute, University of Oxford, Oxford, Oxfordshire, OX3 7LF, UK
| | - Gavin Band
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, OX3 7BN, UK.,Parasites and Microbes Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK
| | - Rosalind M Harding
- Departments of Zoology and Statistics, University of Oxford, Oxford, Oxfordshire, OX1 3SZ, UK
| | - Kirk A Rockett
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, OX3 7BN, UK.,Parasites and Microbes Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SA, UK
| | - Thomas N Williams
- Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, PO BOX 230-80108, Kenya.,Department of Infectious Diseases, Imperial College Faculty of Medicine, London, W2 1NY, UK
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11
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Watson JA, Ndila CM, Uyoga S, Macharia A, Nyutu G, Mohammed S, Ngetsa C, Mturi N, Peshu N, Tsofa B, Rockett K, Leopold S, Kingston H, George EC, Maitland K, Day NPJ, Dondorp AM, Bejon P, Williams TN, Holmes CC, White NJ. Improving statistical power in severe malaria genetic association studies by augmenting phenotypic precision. eLife 2021; 10:e69698. [PMID: 34225842 PMCID: PMC8315799 DOI: 10.7554/elife.69698] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 06/22/2021] [Indexed: 12/14/2022] Open
Abstract
Severe falciparum malaria has substantially affected human evolution. Genetic association studies of patients with clinically defined severe malaria and matched population controls have helped characterise human genetic susceptibility to severe malaria, but phenotypic imprecision compromises discovered associations. In areas of high malaria transmission, the diagnosis of severe malaria in young children and, in particular, the distinction from bacterial sepsis are imprecise. We developed a probabilistic diagnostic model of severe malaria using platelet and white count data. Under this model, we re-analysed clinical and genetic data from 2220 Kenyan children with clinically defined severe malaria and 3940 population controls, adjusting for phenotype mis-labelling. Our model, validated by the distribution of sickle trait, estimated that approximately one-third of cases did not have severe malaria. We propose a data-tilting approach for case-control studies with phenotype mis-labelling and show that this reduces false discovery rates and improves statistical power in genome-wide association studies.
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Affiliation(s)
- James A Watson
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol UniversityBangkokThailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
| | - Carolyne M Ndila
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol UniversityBangkokThailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
| | - Sophie Uyoga
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Alexander Macharia
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Gideon Nyutu
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Shebe Mohammed
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Caroline Ngetsa
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Neema Mturi
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Norbert Peshu
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Benjamin Tsofa
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Kirk Rockett
- The Wellcome Sanger InstituteCambridgeUnited Kingdom
- Wellcome Trust Centre for Human Genetics, University of OxfordOxfordUnited Kingdom
| | - Stije Leopold
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol UniversityBangkokThailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
| | - Hugh Kingston
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol UniversityBangkokThailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
| | - Elizabeth C George
- Medical Research Council Clinical Trials Unit, University College LondonLondonUnited Kingdom
| | - Kathryn Maitland
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
- Institute of Global Health Innovation, Imperial College, LondonLondonUnited Kingdom
| | - Nicholas PJ Day
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol UniversityBangkokThailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
| | - Arjen M Dondorp
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol UniversityBangkokThailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
| | - Philip Bejon
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
| | - Thomas N Williams
- KEMRI-Wellcome Trust Research Programme, Centre for Geographic Medicine Research-CoastKilifiKenya
- Institute of Global Health Innovation, Imperial College, LondonLondonUnited Kingdom
| | - Chris C Holmes
- Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
- Department of Statistics, University of OxfordOxfordUnited Kingdom
| | - Nicholas J White
- Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol UniversityBangkokThailand
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
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12
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Wang L, Balmat TJ, Antonia AL, Constantine FJ, Henao R, Burke TW, Ingham A, McClain MT, Tsalik EL, Ko ER, Ginsburg GS, DeLong MR, Shen X, Woods CW, Hauser ER, Ko DC. An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility. Genome Med 2021; 13:83. [PMID: 34001247 PMCID: PMC8127495 DOI: 10.1186/s13073-021-00904-z] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 05/05/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. RESULTS Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. CONCLUSIONS Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .
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Affiliation(s)
- Liuyang Wang
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, 0049 CARL Building Box 3053, 213 Research Drive, Durham, NC, 27710, USA
| | - Thomas J Balmat
- Duke Research Computing, Duke University, Durham, NC, 27710, USA
| | - Alejandro L Antonia
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, 0049 CARL Building Box 3053, 213 Research Drive, Durham, NC, 27710, USA
| | - Florica J Constantine
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA
| | - Ricardo Henao
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA
| | - Thomas W Burke
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA
| | - Andy Ingham
- Duke Research Computing, Duke University, Durham, NC, 27710, USA
| | - Micah T McClain
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA
- Durham Veterans Affairs Health Care System, Durham, NC, 27705, USA
- Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, NC, 27710, USA
| | - Ephraim L Tsalik
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, 0049 CARL Building Box 3053, 213 Research Drive, Durham, NC, 27710, USA
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA
- Durham Veterans Affairs Health Care System, Durham, NC, 27705, USA
- Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, NC, 27710, USA
| | - Emily R Ko
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA
- Department of Hospital Medicine, Duke Regional Hospital, Durham, NC, 27705, USA
| | - Geoffrey S Ginsburg
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA
| | - Mark R DeLong
- Duke Research Computing, Duke University, Durham, NC, 27710, USA
| | - Xiling Shen
- Department of Biomedical Engineering, Woo Center for Big Data and Precision Health, Duke University, Durham, NC, 27710, USA
| | - Christopher W Woods
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27710, USA
- Durham Veterans Affairs Health Care System, Durham, NC, 27705, USA
- Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, NC, 27710, USA
| | - Elizabeth R Hauser
- Duke Molecular Physiology Institute and Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, 27710, USA
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, NC, 27705, USA
| | - Dennis C Ko
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, 0049 CARL Building Box 3053, 213 Research Drive, Durham, NC, 27710, USA.
- Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, NC, 27710, USA.
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13
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Esoh KK, Apinjoh TO, Nyanjom SG, Wonkam A, Chimusa ER, Amenga-Etego L, Amambua-Ngwa A, Achidi EA. Fine scale human genetic structure in three regions of Cameroon reveals episodic diversifying selection. Sci Rep 2021; 11:1039. [PMID: 33441574 PMCID: PMC7807043 DOI: 10.1038/s41598-020-79124-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 10/28/2020] [Indexed: 01/29/2023] Open
Abstract
Inferences from genetic association studies rely largely on the definition and description of the underlying populations that highlight their genetic similarities and differences. The clustering of human populations into subgroups (population structure) can significantly confound disease associations. This study investigated the fine-scale genetic structure within Cameroon that may underlie disparities observed with Cameroonian ethnicities in malaria genome-wide association studies in sub-Saharan Africa. Genotype data of 1073 individuals from three regions and three ethnic groups in Cameroon were analyzed using measures of genetic proximity to ascertain fine-scale genetic structure. Model-based clustering revealed distinct ancestral proportions among the Bantu, Semi-Bantu and Foulbe ethnic groups, while haplotype-based coancestry estimation revealed possible longstanding and ongoing sympatric differentiation among individuals of the Foulbe ethnic group, and their Bantu and Semi-Bantu counterparts. A genome scan found strong selection signatures in the HLA gene region, confirming longstanding knowledge of natural selection on this genomic region in African populations following immense disease pressure. Signatures of selection were also observed in the HBB gene cluster, a genomic region known to be under strong balancing selection in sub-Saharan Africa due to its co-evolution with malaria. This study further supports the role of evolution in shaping genomes of Cameroonian populations and reveals fine-scale hierarchical structure among and within Cameroonian ethnicities that may impact genetic association studies in the country.
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Affiliation(s)
- Kevin K Esoh
- Department of Biochemistry, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000, Nairobi, City Square, Kenya
| | - Tobias O Apinjoh
- Department of Biochemistry and Molecular Biology, University of Buea, P.O. Box 63, Buea, South West Region, Cameroon.
| | - Steven G Nyanjom
- Department of Biochemistry, Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62000, Nairobi, City Square, Kenya
| | - Ambroise Wonkam
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Health Sciences Campus, Anzio Rd, Observatory, 7925, South Africa
| | - Emile R Chimusa
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Health Sciences Campus, Anzio Rd, Observatory, 7925, South Africa
| | - Lucas Amenga-Etego
- West African Centre for Cell Biology of Infectious Pathogens, University of Ghana, Legon, Accra, Ghana
| | | | - Eric A Achidi
- Department of Biochemistry and Molecular Biology, University of Buea, P.O. Box 63, Buea, South West Region, Cameroon
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14
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Hoh BP, Rahman TA. The indigenous populations as the model by nature to understand human genomic-phenomics interactions. QUANTITATIVE BIOLOGY 2021. [DOI: 10.15302/j-qb-021-0251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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15
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Wang L, Balmat TJ, Antonia AL, Constantine FJ, Henao R, Burke TW, Ingham A, McClain MT, Tsalik EL, Ko ER, Ginsburg GS, DeLong MR, Shen X, Woods CW, Hauser ER, Ko DC. An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.12.20.20248572. [PMID: 33398303 PMCID: PMC7781346 DOI: 10.1101/2020.12.20.20248572] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches.
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Affiliation(s)
- Liuyang Wang
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC 27710, USA
| | | | - Alejandro L. Antonia
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC 27710, USA
| | - Florica J. Constantine
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27710, USA
| | - Ricardo Henao
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27710, USA
| | - Thomas W. Burke
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27710, USA
| | - Andy Ingham
- Duke Research Computing, Duke University, Durham, NC 27710, USA
| | - Micah T. McClain
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27710, USA
- Durham Veterans Affairs Health Care System, Durham, NC 27705, USA
- Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
| | - Ephraim L. Tsalik
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC 27710, USA
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27710, USA
- Durham Veterans Affairs Health Care System, Durham, NC 27705, USA
- Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
| | - Emily R. Ko
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27710, USA
- Department of Hospital Medicine, Duke Regional Hospital, Durham, NC, 27705, USA
| | - Geoffrey S. Ginsburg
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27710, USA
| | - Mark R. DeLong
- Duke Research Computing, Duke University, Durham, NC 27710, USA
| | - Xiling Shen
- Department of Biomedical Engineering, Woo Center for Big Data and Precision Health, Duke University, Durham, NC 27710, USA
| | - Christopher W. Woods
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27710, USA
- Durham Veterans Affairs Health Care System, Durham, NC 27705, USA
- Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
| | - Elizabeth R. Hauser
- Duke Molecular Physiology Institute and Department of Biostatistics and Bioinformatics, Duke University Medical Center Durham, NC 27710, USA
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, NC 27705, USA
| | - Dennis C. Ko
- Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC 27710, USA
- Division of Infectious Diseases, Department of Medicine, Duke University Medical Center, Durham, NC 27710, USA
- Lead contact
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16
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Ndila CM, Nyirongo V, Macharia AW, Jeffreys AE, Rowlands K, Hubbart C, Busby GBJ, Band G, Harding RM, Rockett KA, Williams TN. Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α3.7I form of α-thalassaemia using genome-wide microarray data. Wellcome Open Res 2020; 5:287. [DOI: 10.12688/wellcomeopenres.16320.1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/26/2020] [Indexed: 11/20/2022] Open
Abstract
Background: The -α3.7I-thalassaemia deletion is very common throughout Africa because it protects against malaria. When undertaking studies to investigate human genetic adaptations to malaria or other diseases, it is important to account for any confounding effects of α-thalassaemia to rule out spurious associations. Methods: In this study we have used direct α-thalassaemia genotyping to understand why GWAS data from a large malaria association study in Kilifi Kenya did not identify the α-thalassaemia signal. We then explored the potential use of a number of new approaches to using GWAS data for imputing α-thalassaemia as an alternative to direct genotyping by PCR. Results: We found very low linkage-disequilibrium of the directly typed data with the GWAS SNP markers around α-thalassaemia and across the haemoglobin-alpha (HBA) gene region, which along with a complex haplotype structure, could explain the lack of an association signal from the GWAS SNP data. Some indirect typing methods gave results that were in broad agreement with those derived from direct genotyping and could identify an association signal, but none were sufficiently accurate to allow correct interpretation compared with direct typing, leading to confusing or erroneous results. Conclusions: We conclude that going forwards, direct typing methods such as PCR will still be required to account for α-thalassaemia in GWAS studies.
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17
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Abstract
Malaria has been the pre-eminent cause of early mortality in many parts of the world throughout much of the last five thousand years and, as a result, it is the strongest force for selective pressure on the human genome yet described. Around one third of the variability in the risk of severe and complicated malaria is now explained by additive host genetic effects. Many individual variants have been identified that are associated with malaria protection, but the most important all relate to the structure or function of red blood cells. They include the classical polymorphisms that cause sickle cell trait, α-thalassaemia, G6PD deficiency, and the major red cell blood group variants. More recently however, with improving technology and experimental design, others have been identified that include the Dantu blood group variant, polymorphisms in the red cell membrane protein ATP2B4, and several variants related to the immune response. Characterising how these genes confer their effects could eventually inform novel therapeutic approaches to combat malaria. Nevertheless, all together, only a small proportion of the heritable component of malaria resistance can be explained by the variants described so far, underscoring its complex genetic architecture and the need for continued research.
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Affiliation(s)
- Silvia N Kariuki
- Department of Epidemiology, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.
| | - Thomas N Williams
- Department of Epidemiology, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.
- Department of Medicine, Imperial College of Science and Technology, London, UK.
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18
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Tanigawa Y, Wainberg M, Karjalainen J, Kiiskinen T, Venkataraman G, Lemmelä S, Turunen JA, Graham RR, Havulinna AS, Perola M, Palotie A, Daly MJ, Rivas MA. Rare protein-altering variants in ANGPTL7 lower intraocular pressure and protect against glaucoma. PLoS Genet 2020; 16:e1008682. [PMID: 32369491 PMCID: PMC7199928 DOI: 10.1371/journal.pgen.1008682] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Accepted: 02/18/2020] [Indexed: 12/17/2022] Open
Abstract
Protein-altering variants that are protective against human disease provide in vivo validation of therapeutic targets. Here we use genotyping data from UK Biobank (n = 337,151 unrelated White British individuals) and FinnGen (n = 176,899) to conduct a search for protein-altering variants conferring lower intraocular pressure (IOP) and protection against glaucoma. Through rare protein-altering variant association analysis, we find a missense variant in ANGPTL7 in UK Biobank (rs28991009, p.Gln175His, MAF = 0.8%, genotyped in 82,253 individuals with measured IOP and an independent set of 4,238 glaucoma patients and 250,660 controls) that significantly lowers IOP (β = -0.53 and -0.67 mmHg for heterozygotes, -3.40 and -2.37 mmHg for homozygotes, P = 5.96 x 10-9 and 1.07 x 10-13 for corneal compensated and Goldman-correlated IOP, respectively) and is associated with 34% reduced risk of glaucoma (P = 0.0062). In FinnGen, we identify an ANGPTL7 missense variant at a greater than 50-fold increased frequency in Finland compared with other populations (rs147660927, p.Arg220Cys, MAF Finland = 4.3%), which was genotyped in 6,537 glaucoma patients and 170,362 controls and is associated with a 29% lower glaucoma risk (P = 1.9 x 10-12 for all glaucoma types and also protection against its subtypes including exfoliation, primary open-angle, and primary angle-closure). We further find three rarer variants in UK Biobank, including a protein-truncating variant, which confer a strong composite lowering of IOP (P = 0.0012 and 0.24 for Goldman-correlated and corneal compensated IOP, respectively), suggesting the protective mechanism likely resides in the loss of interaction or function. Our results support inhibition or down-regulation of ANGPTL7 as a therapeutic strategy for glaucoma.
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Affiliation(s)
- Yosuke Tanigawa
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, United States of America
| | - Michael Wainberg
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, United States of America
| | - Juha Karjalainen
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Tuomo Kiiskinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Guhan Venkataraman
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, United States of America
| | - Susanna Lemmelä
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Joni A. Turunen
- Department of Ophthalmology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, Biomedicum Helsinki, Helsinki, Finland
| | - Robert R. Graham
- Maze Therapeutics, South San Francisco, California, United States of America
| | - Aki S. Havulinna
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Aarno Palotie
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | | | - Mark J. Daly
- Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Manuel A. Rivas
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, United States of America
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19
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Damena D, Chimusa ER. Genome-wide heritability analysis of severe malaria resistance reveals evidence of polygenic inheritance. Hum Mol Genet 2020; 29:168-176. [PMID: 31691794 PMCID: PMC7416678 DOI: 10.1093/hmg/ddz258] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 10/14/2019] [Accepted: 10/23/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Estimating single nucleotide polymorphism (SNP)-heritability (h2g) of severe malaria resistance and its distribution across the genome might shed new light in to the underlying biology. METHOD We investigated h2g of severe malaria resistance from a genome-wide association study (GWAS) dataset (sample size = 11 657). We estimated the h2g and partitioned in to chromosomes, allele frequencies and annotations using the genetic relationship-matrix restricted maximum likelihood approach. We further examined non-cell type-specific and cell type-specific enrichments from GWAS-summary statistics. RESULTS The h2g of severe malaria resistance was estimated at 0.21 (se = 0.05, P = 2.7 × 10-5), 0.20 (se = 0.05, P = 7.5 × 10-5) and 0.17 (se = 0.05, P = 7.2 × 10-4) in Gambian, Kenyan and Malawi populations, respectively. A comparable range of h2g [0.21 (se = 0.02, P < 1 × 10-5)] was estimated from GWAS-summary statistics meta-analysed across the three populations. Partitioning analysis from raw genotype data showed significant enrichment of h2g in genic SNPs while summary statistics analysis suggests evidences of enrichment in multiple categories. Supporting the polygenic inheritance, the h2g of severe malaria resistance is distributed across the chromosomes and allelic frequency spectrum. However, the h2g is disproportionately concentrated on three chromosomes (chr 5, 11 and 20), suggesting cost-effectiveness of targeting these chromosomes in future malaria genomic sequencing studies. CONCLUSION We report for the first time that the heritability of malaria resistance is largely ascribed by common SNPs and the causal variants are overrepresented in protein coding regions of the genome. Further studies with larger sample sizes are needed to better understand the underpinning genetics of severe malaria resistance.
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Affiliation(s)
- Delesa Damena
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine University of Cape Town, Private Bag, Rondebosch, 7700 Cape Town, South Africa
| | - Emile R Chimusa
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine University of Cape Town, Private Bag, Rondebosch, 7700 Cape Town, South Africa
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20
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Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania. Nat Commun 2019; 10:5732. [PMID: 31844061 PMCID: PMC6914791 DOI: 10.1038/s41467-019-13480-z] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 11/11/2019] [Indexed: 12/31/2022] Open
Abstract
The human genetic factors that affect resistance to infectious disease are poorly understood. Here we report a genome-wide association study in 17,000 severe malaria cases and population controls from 11 countries, informed by sequencing of family trios and by direct typing of candidate loci in an additional 15,000 samples. We identify five replicable associations with genome-wide levels of evidence including a newly implicated variant on chromosome 6. Jointly, these variants account for around one-tenth of the heritability of severe malaria, which we estimate as ~23% using genome-wide genotypes. We interrogate available functional data and discover an erythroid-specific transcription start site underlying the known association in ATP2B4, but are unable to identify a likely causal mechanism at the chromosome 6 locus. Previously reported HLA associations do not replicate in these samples. This large dataset will provide a foundation for further research on the genetic determinants of malaria resistance in diverse populations. Four genome-wide associated loci are currently known for malaria susceptibility. Here, the authors expand on earlier work by combining data from 11 malaria-endemic countries and additional population sequencing informing an African-enriched imputation reference panel, with findings including a previously unreported association on chromosome 6.
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21
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Deng L, Lou H, Zhang X, Thiruvahindrapuram B, Lu D, Marshall CR, Liu C, Xie B, Xu W, Wong LP, Yew CW, Farhang A, Ong RTH, Hoque MZ, Thuhairah AR, Jong B, Phipps ME, Scherer SW, Teo YY, Kumar SV, Hoh BP, Xu S. Analysis of five deep-sequenced trio-genomes of the Peninsular Malaysia Orang Asli and North Borneo populations. BMC Genomics 2019; 20:842. [PMID: 31718558 PMCID: PMC6852992 DOI: 10.1186/s12864-019-6226-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 10/25/2019] [Indexed: 12/18/2022] Open
Abstract
Background Recent advances in genomic technologies have facilitated genome-wide investigation of human genetic variations. However, most efforts have focused on the major populations, yet trio genomes of indigenous populations from Southeast Asia have been under-investigated. Results We analyzed the whole-genome deep sequencing data (~ 30×) of five native trios from Peninsular Malaysia and North Borneo, and characterized the genomic variants, including single nucleotide variants (SNVs), small insertions and deletions (indels) and copy number variants (CNVs). We discovered approximately 6.9 million SNVs, 1.2 million indels, and 9000 CNVs in the 15 samples, of which 2.7% SNVs, 2.3% indels and 22% CNVs were novel, implying the insufficient coverage of population diversity in existing databases. We identified a higher proportion of novel variants in the Orang Asli (OA) samples, i.e., the indigenous people from Peninsular Malaysia, than that of the North Bornean (NB) samples, likely due to more complex demographic history and long-time isolation of the OA groups. We used the pedigree information to identify de novo variants and estimated the autosomal mutation rates to be 0.81 × 10− 8 – 1.33 × 10− 8, 1.0 × 10− 9 – 2.9 × 10− 9, and ~ 0.001 per site per generation for SNVs, indels, and CNVs, respectively. The trio-genomes also allowed for haplotype phasing with high accuracy, which serves as references to the future genomic studies of OA and NB populations. In addition, high-frequency inherited CNVs specific to OA or NB were identified. One example is a 50-kb duplication in DEFA1B detected only in the Negrito trios, implying plausible effects on host defense against the exposure of diverse microbial in tropical rainforest environment of these hunter-gatherers. The CNVs shared between OA and NB groups were much fewer than those specific to each group. Nevertheless, we identified a 142-kb duplication in AMY1A in all the 15 samples, and this gene is associated with the high-starch diet. Moreover, novel insertions shared with archaic hominids were identified in our samples. Conclusion Our study presents a full catalogue of the genome variants of the native Malaysian populations, which is a complement of the genome diversity in Southeast Asians. It implies specific population history of the native inhabitants, and demonstrated the necessity of more genome sequencing efforts on the multi-ethnic native groups of Malaysia and Southeast Asia.
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Affiliation(s)
- Lian Deng
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Haiyi Lou
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xiaoxi Zhang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | | | - Dongsheng Lu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Christian R Marshall
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada.,Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.,Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Chang Liu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Bo Xie
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wanxing Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Lai-Ping Wong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore
| | - Chee-Wei Yew
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Aghakhanian Farhang
- Jefrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Sunway, 46150, Subang Jaya, Selangor, Malaysia.,Tropical Medicine and Biology Platform, Monash University Malaysia, Jalan Lagoon Selatan, 46150 Sunway, Subang Jaya, Selangor, Malaysia
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore
| | - Mohammad Zahirul Hoque
- Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Abdul Rahman Thuhairah
- Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, 47000 Sg Buloh, Subang Jaya, Selangor, Malaysia
| | - Bhak Jong
- Personal Genomics Institute, Genome Research Foundation, Suwon, Republic of Korea.,Geromics, Ulsan, 44919, Republic of Korea.,Biomedical Engineering Department, The Genomics Institute, UNIST, Ulsan, Republic of Korea
| | - Maude E Phipps
- Tropical Medicine and Biology Platform, Monash University Malaysia, Jalan Lagoon Selatan, 46150 Sunway, Subang Jaya, Selangor, Malaysia
| | - Stephen W Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada.,Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.,Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, 117456, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore.,Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore
| | - Subbiah Vijay Kumar
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
| | - Boon-Peng Hoh
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Faculty of Medicine and Health Sciences, UCSI University, Jalan Menara Gading, Taman Connaught, Cheras, 56000, Kuala Lumpur, Malaysia.
| | - Shuhua Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China. .,Collaborative Innovation Center of Genetics and Development, Shanghai, 200438, China. .,Human Phenome Institute, Fudan University, Shanghai, 201203, China.
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Thiam A, Sanka M, Ndiaye Diallo R, Torres M, Mbengue B, Nunez NF, Thiam F, Diop G, Victorero G, Nguyen C, Dieye A, Rihet P. Gene expression profiling in blood from cerebral malaria patients and mild malaria patients living in Senegal. BMC Med Genomics 2019; 12:148. [PMID: 31666081 PMCID: PMC6821028 DOI: 10.1186/s12920-019-0599-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Accepted: 10/09/2019] [Indexed: 01/06/2023] Open
Abstract
Background Plasmodium falciparum malaria remains a major health problem in Africa. The mechanisms of pathogenesis are not fully understood. Transcriptomic studies may provide new insights into molecular pathways involved in the severe form of the disease. Methods Blood transcriptional levels were assessed in patients with cerebral malaria, non-cerebral malaria, or mild malaria by using microarray technology to look for gene expression profiles associated with clinical status. Multi-way ANOVA was used to extract differentially expressed genes. Network and pathways analyses were used to detect enrichment for biological pathways. Results We identified a set of 443 genes that were differentially expressed in the three patient groups after applying a false discovery rate of 10%. Since the cerebral patients displayed a particular transcriptional pattern, we focused our analysis on the differences between cerebral malaria patients and mild malaria patients. We further found 842 differentially expressed genes after applying a false discovery rate of 10%. Unsupervised hierarchical clustering of cerebral malaria-informative genes led to clustering of the cerebral malaria patients. The support vector machine method allowed us to correctly classify five out of six cerebral malaria patients and six of six mild malaria patients. Furthermore, the products of the differentially expressed genes were mapped onto a human protein-protein network. This led to the identification of the proteins with the highest number of interactions, including GSK3B, RELA, and APP. The enrichment analysis of the gene functional annotation indicates that genes involved in immune signalling pathways play a role in the occurrence of cerebral malaria. These include BCR-, TCR-, TLR-, cytokine-, FcεRI-, and FCGR- signalling pathways and natural killer cell cytotoxicity pathways, which are involved in the activation of immune cells. In addition, our results revealed an enrichment of genes involved in Alzheimer’s disease. Conclusions In the present study, we examine a set of genes whose expression differed in cerebral malaria patients and mild malaria patients. Moreover, our results provide new insights into the potential effect of the dysregulation of gene expression in immune pathways. Host genetic variation may partly explain such alteration of gene expression. Further studies are required to investigate this in African populations.
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Affiliation(s)
- Alassane Thiam
- Unité d'Immunogénétique, Institut Pasteur de Dakar, Dakar, Sénégal
| | - Michel Sanka
- Aix Marseille Univ, INSERM, TAGC UMR U1090, 163 Av de Luminy, 13288, Marseille, cedex 9, France
| | - Rokhaya Ndiaye Diallo
- Service de Génétique Humaine, Faculté de Médecine, de Pharmacie et d'Odontostomatologie, UCAD, Dakar, Sénégal
| | - Magali Torres
- Aix Marseille Univ, INSERM, TAGC UMR U1090, 163 Av de Luminy, 13288, Marseille, cedex 9, France
| | - Babacar Mbengue
- Service Immunologie, Faculte de Medecine, Université Cheikh Anta Diop de Dakar, Dakar, Sénégal
| | - Nicolas Fernandez Nunez
- Aix Marseille Univ, INSERM, TAGC UMR U1090, 163 Av de Luminy, 13288, Marseille, cedex 9, France
| | - Fatou Thiam
- Département de Génie chimique et biologie, Ecole Supérieure Polytechnique, Université Cheikh Anta Diop de Dakar, Dakar, Sénégal
| | - Gora Diop
- Unité d'Immunogénétique, Institut Pasteur de Dakar, Dakar, Sénégal.,Département de Biologie animale, Faculté des Sciences et Techniques, Université Cheikh Anta Diop de Dakar, Dakar, Sénégal
| | - Geneviève Victorero
- Aix Marseille Univ, INSERM, TAGC UMR U1090, 163 Av de Luminy, 13288, Marseille, cedex 9, France
| | - Catherine Nguyen
- Aix Marseille Univ, INSERM, TAGC UMR U1090, 163 Av de Luminy, 13288, Marseille, cedex 9, France
| | - Alioune Dieye
- Unité d'Immunogénétique, Institut Pasteur de Dakar, Dakar, Sénégal.,Service Immunologie, Faculte de Medecine, Université Cheikh Anta Diop de Dakar, Dakar, Sénégal
| | - Pascal Rihet
- Aix Marseille Univ, INSERM, TAGC UMR U1090, 163 Av de Luminy, 13288, Marseille, cedex 9, France.
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23
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First genome-wide association study of non-severe malaria in two birth cohorts in Benin. Hum Genet 2019; 138:1341-1357. [PMID: 31667592 DOI: 10.1007/s00439-019-02079-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 10/22/2019] [Indexed: 12/16/2022]
Abstract
Recent research efforts to identify genes involved in malaria susceptibility using genome-wide approaches have focused on severe malaria. Here, we present the first GWAS on non-severe malaria designed to identify genetic variants involved in innate immunity or innate resistance mechanisms. Our study was performed on two cohorts of infants from southern Benin (525 and 250 individuals used as discovery and replication cohorts, respectively) closely followed from birth to 18-24 months of age, with an assessment of a space- and time-dependent environmental risk of exposure. Both the recurrence of mild malaria attacks and the recurrence of malaria infections as a whole (symptomatic and asymptomatic) were considered. Post-GWAS functional analyses were performed using positional, eQTL, and chromatin interaction mapping to identify the genes underlying association signals. Our study highlights a role of PTPRT, a tyrosine phosphatase receptor involved in STAT3 pathway, in the protection against both mild malaria attacks and malaria infections (p = 9.70 × 10-8 and p = 1.78 × 10-7, respectively, in the discovery cohort). Strong statistical support was also found for a role of MYLK4 (meta-analysis, p = 5.29 × 10-8 with malaria attacks), and for several other genes, whose biological functions are relevant in malaria infection. Results shows that GWAS on non-severe malaria can successfully identify new candidate genes and inform physiological mechanisms underlying natural protection against malaria.
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24
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Ansari MA, Aranday-Cortes E, Ip CL, da Silva Filipe A, Lau SH, Bamford C, Bonsall D, Trebes A, Piazza P, Sreenu V, Cowton VM, Hudson E, Bowden R, Patel AH, Foster GR, Irving WL, Agarwal K, Thomson EC, Simmonds P, Klenerman P, Holmes C, Barnes E, Spencer CC, McLauchlan J, Pedergnana V. Interferon lambda 4 impacts the genetic diversity of hepatitis C virus. eLife 2019; 8:42463. [PMID: 31478835 PMCID: PMC6721795 DOI: 10.7554/elife.42463] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 08/08/2019] [Indexed: 12/15/2022] Open
Abstract
Hepatitis C virus (HCV) is a highly variable pathogen that frequently establishes chronic infection. This genetic variability is affected by the adaptive immune response but the contribution of other host factors is unclear. Here, we examined the role played by interferon lambda-4 (IFN-λ4) on HCV diversity; IFN-λ4 plays a crucial role in spontaneous clearance or establishment of chronicity following acute infection. We performed viral genome-wide association studies using human and viral data from 485 patients of white ancestry infected with HCV genotype 3a. We demonstrate that combinations of host genetic variants, which determine IFN-λ4 protein production and activity, influence amino acid variation across the viral polyprotein - not restricted to specific viral proteins or HLA restricted epitopes - and modulate viral load. We also observed an association with viral di-nucleotide proportions. These results support a direct role for IFN-λ4 in exerting selective pressure across the viral genome, possibly by a novel mechanism.
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Affiliation(s)
- M Azim Ansari
- Wellcome Centre Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Elihu Aranday-Cortes
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | - Camilla Lc Ip
- Wellcome Centre Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Ana da Silva Filipe
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | - Siu Hin Lau
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | - Connor Bamford
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | - David Bonsall
- Nuffield Department of Medicine and the Oxford NIHR BRC, University of Oxford, Oxford, United Kingdom
| | - Amy Trebes
- Wellcome Centre Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Paolo Piazza
- Wellcome Centre Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Vattipally Sreenu
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | - Vanessa M Cowton
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | | | - Emma Hudson
- Nuffield Department of Medicine and the Oxford NIHR BRC, University of Oxford, Oxford, United Kingdom
| | - Rory Bowden
- Wellcome Centre Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Arvind H Patel
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | - Graham R Foster
- Blizard Institute, Queen Mary University, London, United Kingdom
| | - William L Irving
- National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham, United Kingdom
| | - Kosh Agarwal
- Institute of Liver Studies, King's College Hospital, London, United Kingdom
| | - Emma C Thomson
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | - Peter Simmonds
- Nuffield Department of Medicine and the Oxford NIHR BRC, University of Oxford, Oxford, United Kingdom
| | - Paul Klenerman
- Nuffield Department of Medicine and the Oxford NIHR BRC, University of Oxford, Oxford, United Kingdom
| | - Chris Holmes
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Eleanor Barnes
- Nuffield Department of Medicine and the Oxford NIHR BRC, University of Oxford, Oxford, United Kingdom
| | - Chris Ca Spencer
- Wellcome Centre Human Genetics, University of Oxford, Oxford, United Kingdom
| | - John McLauchlan
- MRC-University of Glasgow Centre for Virus Research, Sir Michael Stoker Building, Glasgow, United Kingdom
| | - Vincent Pedergnana
- Wellcome Centre Human Genetics, University of Oxford, Oxford, United Kingdom.,Laboratoire MIVEGEC (UMR CNRS 5290, IRD, UM), Montpellier, France
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25
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Brzozowska MM, Havula E, Allen RB, Cox MP. Genetics, adaptation to environmental changes and archaic admixture in the pathogenesis of diabetes mellitus in Indigenous Australians. Rev Endocr Metab Disord 2019; 20:321-332. [PMID: 31278514 DOI: 10.1007/s11154-019-09505-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Indigenous Australians are particularly affected by type 2 diabetes mellitus (T2D) due to both their genetic susceptibility and a range of environmental and lifestyle risk factors. Recent genetic studies link predisposition to some diseases, including T2D, to alleles acquired from archaic hominins, such as Neanderthals and Denisovans, which persist in the genomes of modern humans today. Indo-Pacific human populations, including Indigenous Australians, remain extremely underrepresented in genomic research with a paucity of data examining the impact of Denisovan or Neanderthal lineages on human phenotypes in Oceania. The few genetic studies undertaken emphasize the uniqueness and antiquity of Indigenous Australian genomes, with possibly the largest proportion of Denisovan ancestry of any population in the world. In this review, we focus on the potential contributions of ancient genes/pathways to modern human phenotypes, while also highlighting the evolutionary roles of genetic adaptation to dietary and environmental changes associated with an adopted Western lifestyle. We discuss the role of genetic and epigenetic factors in the pathogenesis of T2D in understudied Indigenous Australians, including the potential impact of archaic gene lineages on this disease. Finally, we propose that greater understanding of the underlying genetic predisposition may contribute to the clinical efficacy of diabetes management in Indigenous Australians. We suggest that improved identification of T2D risk variants in Oceania is needed. Such studies promise to clarify how genetic and phenotypic differences vary between populations and, crucially, provide novel targets for personalised medical therapies in currently marginalized groups.
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Affiliation(s)
- Malgorzata Monika Brzozowska
- Endocrinology Department, Sutherland Hospital, Sydney, New South Wales, Australia.
- St George & Sutherland Hospital Clinical School, University of New South Wales, Sydney, Australia.
| | - Essi Havula
- School of Life and Environmental Sciences, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Richard Benjamin Allen
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Murray P Cox
- Statistics and Bioinformatics Group, School of Fundamental Sciences, Massey University, Palmerston North, 4410, New Zealand
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26
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Damena D, Denis A, Golassa L, Chimusa ER. Genome-wide association studies of severe P. falciparum malaria susceptibility: progress, pitfalls and prospects. BMC Med Genomics 2019; 12:120. [PMID: 31409341 PMCID: PMC6693204 DOI: 10.1186/s12920-019-0564-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2018] [Accepted: 07/29/2019] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND P. falciparum malaria has been recognized as one of the prominent evolutionary selective forces of human genome that led to the emergence of multiple host protective alleles. A comprehensive understanding of the genetic bases of severe malaria susceptibility and resistance can potentially pave ways to the development of new therapeutics and vaccines. Genome-wide association studies (GWASs) have recently been implemented in malaria endemic areas and identified a number of novel association genetic variants. However, there are several open questions around heritability, epistatic interactions, genetic correlations and associated molecular pathways among others. Here, we assess the progress and pitfalls of severe malaria susceptibility GWASs and discuss the biology of the novel variants. RESULTS We obtained all severe malaria susceptibility GWASs published thus far and accessed GWAS dataset of Gambian populations from European Phenome Genome Archive (EGA) through the MalariaGen consortium standard data access protocols. We noticed that, while some of the well-known variants including HbS and ABO blood group were replicated across endemic populations, only few novel variants were convincingly identified and their biological functions remain to be understood. We estimated SNP-heritability of severe malaria at 20.1% in Gambian populations and showed how advanced statistical genetic analytic methods can potentially be implemented in malaria susceptibility studies to provide useful functional insights. CONCLUSIONS The ultimate goal of malaria susceptibility study is to discover a novel causal biological pathway that provide protections against severe malaria; a fundamental step towards translational medicine such as development of vaccine and new therapeutics. Beyond singe locus analysis, the future direction of malaria susceptibility requires a paradigm shift from single -omics to multi-stage and multi-dimensional integrative functional studies that combines multiple data types from the human host, the parasite, the mosquitoes and the environment. The current biotechnological and statistical advances may eventually lead to the feasibility of systems biology studies and revolutionize malaria research.
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Affiliation(s)
- Delesa Damena
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Private Bag, Rondebosch, Cape Town, 7700 South Africa
| | - Awany Denis
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Private Bag, Rondebosch, Cape Town, 7700 South Africa
| | - Lemu Golassa
- Aklilu Lema Institute of Pathobiology, Addis Ababa University, PO box 1176, Addis Ababa, Ethiopia
| | - Emile R. Chimusa
- Division of Human Genetics, Department of Pathology, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Private Bag, Rondebosch, Cape Town, 7700 South Africa
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27
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Penha-Gonçalves C. Genetics of Malaria Inflammatory Responses: A Pathogenesis Perspective. Front Immunol 2019; 10:1771. [PMID: 31417551 PMCID: PMC6682681 DOI: 10.3389/fimmu.2019.01771] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 07/15/2019] [Indexed: 12/27/2022] Open
Abstract
Despite significant progress in combating malaria in recent years the burden of severe disease and death due to Plasmodium infections remains a global public health concern. Only a fraction of infected people develops severe clinical syndromes motivating a longstanding search for genetic determinants of malaria severity. Strong genetic effects have been repeatedly ascribed to mutations and allelic variants of proteins expressed in red blood cells but the role of inflammatory response genes in disease pathogenesis has been difficult to discern. We revisited genetic evidence provided by inflammatory response genes that have been repeatedly associated to malaria, namely TNF, NOS2, IFNAR1, HMOX1, TLRs, CD36, and CD40LG. This highlighted specific genetic variants having opposing roles in the development of distinct malaria clinical outcomes and unveiled diverse levels of genetic heterogeneity that shaped the complex association landscape of inflammatory response genes with malaria. However, scrutinizing genetic effects of individual variants corroborates a pathogenesis model where pro-inflammatory genetic variants acting in early infection stages contribute to resolve infection but at later stages confer increased vulnerability to severe organ dysfunction driven by tissue inflammation. Human genetics studies are an invaluable tool to find genes and molecular pathways involved in the inflammatory response to malaria but their precise roles in disease pathogenesis are still unexploited. Genome editing in malaria experimental models and novel genotyping-by-sequencing techniques are promising approaches to delineate the relevance of inflammatory response gene variants in the natural history of infection thereby will offer new rational angles on adjuvant therapeutics for prevention and clinical management of severe malaria.
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Trochet H, Pirinen M, Band G, Jostins L, McVean G, Spencer CCA. Bayesian meta-analysis across genome-wide association studies of diverse phenotypes. Genet Epidemiol 2019; 43:532-547. [PMID: 30920090 DOI: 10.1002/gepi.22202] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Revised: 03/01/2019] [Accepted: 03/05/2019] [Indexed: 11/09/2022]
Abstract
Genome-wide association studies (GWAS) are a powerful tool for understanding the genetic basis of diseases and traits, but most studies have been conducted in isolation, with a focus on either a single or a set of closely related phenotypes. We describe MetABF, a simple Bayesian framework for performing integrative meta-analysis across multiple GWAS using summary statistics. The approach is applicable across a wide range of study designs and can increase the power by 50% compared with standard frequentist tests when only a subset of studies have a true effect. We demonstrate its utility in a meta-analysis of 20 diverse GWAS which were part of the Wellcome Trust Case Control Consortium 2. The novelty of the approach is its ability to explore, and assess the evidence for a range of possible true patterns of association across studies in a computationally efficient framework.
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Affiliation(s)
- Holly Trochet
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Institut de Cardiologie de Montréal (Centre de Recherche), Université de Montréal, Montréal, Québec, Canada
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Mathematics and Statistics, Helsinki Institute for Information Technology HIIT, University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Gavin Band
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Luke Jostins
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.,Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK.,Christ Church, University of Oxford, Oxford, UK
| | - Gilean McVean
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Chris C A Spencer
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
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Polfus LM, Raffield LM, Wheeler MM, Tracy RP, Lange LA, Lettre G, Miller A, Correa A, Bowler RP, Bis JC, Salimi S, Jenny NS, Pankratz N, Wang B, Preuss MH, Zhou L, Moscati A, Nadkarni GN, Loos RJF, Zhong X, Li B, Johnsen JM, Nickerson DA, Reiner AP, Auer PL. Whole genome sequence association with E-selectin levels reveals loss-of-function variant in African Americans. Hum Mol Genet 2019; 28:515-523. [PMID: 30307499 PMCID: PMC6337694 DOI: 10.1093/hmg/ddy360] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 10/01/2018] [Accepted: 10/07/2018] [Indexed: 12/13/2022] Open
Abstract
E-selectin mediates the rolling of circulating leukocytes during inflammatory processes. Previous genome-wide association studies in European and Asian individuals have identified the ABO locus associated with E-selectin levels. Using Trans-Omics for Precision Medicine whole genome sequencing data in 2249 African Americans (AAs) from the Jackson Heart Study, we examined genome-wide associations with soluble E-selectin levels. In addition to replicating known signals at ABO, we identified a novel association of a common loss-of-function, missense variant in Fucosyltransferase 6 (FUT6; rs17855739,p.Glu274Lys, P = 9.02 × 10-24) with higher soluble E-selectin levels. This variant is considerably more common in populations of African ancestry compared to non-African ancestry populations. We replicated the association of FUT6 p.Glu274Lys with higher soluble E-selectin in an independent population of 748 AAs from the Women's Health Initiative and identified an additional pleiotropic association with vitamin B12 levels. Despite the broad role of both selectins and fucosyltransferases in various inflammatory, immune and cancer-related processes, we were unable to identify any additional disease associations of the FUT6 p.Glu274Lys variant in an electronic medical record-based phenome-wide association scan of over 9000 AAs.
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Affiliation(s)
- Linda M Polfus
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Marsha M Wheeler
- Department of Genome Sciences, University of Washington Center for Mendelian Genomics, Seattle, WA, USA
| | - Russell P Tracy
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Biochemistry, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Leslie A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - Guillaume Lettre
- Department of Medicine, Université de Montréal, Montréal, QC, Canada
- Montreal Heart Institute, Montréal, QC, Canada
| | - Amanda Miller
- Zilber School of Public Health, University of Wisconsin–Milwaukee, Milwaukee, WI, USA
| | - Adolfo Correa
- Department of Pediatrics and Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | | | - Joshua C Bis
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Shabnam Salimi
- School of Medicine, University of Maryland, Baltimore, MD, USA
| | - Nancy Swords Jenny
- Department of Pathology and Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Biqi Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Michael H Preuss
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Lisheng Zhou
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Arden Moscati
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Girish N Nadkarni
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Xue Zhong
- Vanderbilt Genetics Institute, Nashville, TN, USA
| | - Bingshan Li
- Vanderbilt Genetics Institute, Nashville, TN, USA
| | - Jill M Johnsen
- Bloodworks Northwest Research Institute, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington Center for Mendelian Genomics, Seattle, WA, USA
| | - Alex P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Paul L Auer
- Zilber School of Public Health, University of Wisconsin–Milwaukee, Milwaukee, WI, USA
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Hoh BP, Abdul Rahman T, Yusoff K. Natural selection and local adaptation of blood pressure regulation and their perspectives on precision medicine in hypertension. Hereditas 2019; 156:1. [PMID: 30636949 PMCID: PMC6323824 DOI: 10.1186/s41065-019-0080-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2018] [Accepted: 01/01/2019] [Indexed: 01/09/2023] Open
Abstract
Prevalence of hypertension (HTN) varies substantially across different populations. HTN is not only common - affecting at least one third of the world's adult population - but is also the most important driver for cardiovascular diseases. Yet up to a third of hypertensive patients are resistant to therapy, contributed by secondary hypertension but more commonly the hitherto inability to precisely predict response to specific antihypertensive agents. Population and individual genomics information could be useful in guiding the selection and predicting the response to treatment - an approach known as precision medicine. However this cannot be achieved without the knowledge of genetic variations that influence blood pressure (BP). A number of evolutionary factors including population demographics and forces of natural selection may be involved. This article explores some ideas on how natural selection influences BP regulation in ethnically and geographically diverse populations that could lead to them being susceptible to HTN. We explore how such evolutionary factors could impact the implementation of precision medicine in HTN. Finally, in order to ensure the success of precision medicine in HTN, we call for more initiatives to understand the genetic architecture within and between diverse populations with ancestry from different parts of the world, and to precisely classify the intermediate phenotypes of HTN.
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Affiliation(s)
- Boon-Peng Hoh
- 1Faculty of Medicine and Health Sciences, UCSI University, Cheras, 56000 Kuala Lumpur, Malaysia.,2Chinese Academy of Sciences Key Laboratory of Computational Biology, Max Planck Independent Research Group on Population Genomics, CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, CAS, Shanghai, 200031 China
| | - Thuhairah Abdul Rahman
- 3Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, 47000 Sungai Buloh, Selangor Malaysia
| | - Khalid Yusoff
- 1Faculty of Medicine and Health Sciences, UCSI University, Cheras, 56000 Kuala Lumpur, Malaysia
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31
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Thiam A, Baaklini S, Mbengue B, Nisar S, Diarra M, Marquet S, Fall MM, Sanka M, Thiam F, Diallo RN, Torres M, Dieye A, Rihet P. NCR3 polymorphism, haematological parameters, and severe malaria in Senegalese patients. PeerJ 2018; 6:e6048. [PMID: 30533319 PMCID: PMC6282937 DOI: 10.7717/peerj.6048] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 10/31/2018] [Indexed: 12/12/2022] Open
Abstract
Background Host factors, including host genetic variation, have been shown to influence the outcome of Plasmodium falciparum infection. Genome-wide linkage studies have mapped mild malaria resistance genes on chromosome 6p21, whereas NCR3-412 polymorphism (rs2736191) lying within this region was found to be associated with mild malaria. Methods Blood samples were taken from 188 Plasmodium falciparum malaria patients (76 mild malaria patients, 85 cerebral malaria patients, and 27 severe non-cerebral malaria patients). NCR3-412 (rs2736191) was analysed by sequencing, and haematological parameters were measured. Finally, their association with clinical phenotypes was assessed. Results We evidenced an association of thrombocytopenia with both cerebral malaria and severe non-cerebral malaria, and of an association of high leukocyte count with cerebral malaria. Additionally, we found no association of NCR3-412 with either cerebral malaria, severe non-cerebral malaria, or severe malaria after grouping cerebral malaria and severe non-cerebral malaria patients. Conclusions Our results suggest that NCR3 genetic variation has no effect, or only a small effect on the occurrence of severe malaria, although it has been strongly associated with mild malaria. We discuss the biological meaning of these results. Besides, we confirmed the association of thrombocytopenia and high leukocyte count with severe malaria phenotypes.
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Affiliation(s)
- Alassane Thiam
- Unité d'Immunogénétique, Institut Pasteur de Dakar, Dakar, Senegal
| | | | - Babacar Mbengue
- Service d'Immunologie, University Cheikh Anta Diop of Dakar, Dakar, Senegal
| | - Samia Nisar
- Aix Marseille Univ, INSERM, TAGC, Marseille, France
| | - Maryam Diarra
- G4 Biostatistique, Institut Pasteur de Dakar, Dakar, Sénégal
| | | | | | - Michel Sanka
- Aix Marseille Univ, INSERM, TAGC, Marseille, France
| | - Fatou Thiam
- Unité d'Immunogénétique, Institut Pasteur de Dakar, Dakar, Senegal
| | | | | | - Alioune Dieye
- Unité d'Immunogénétique, Institut Pasteur de Dakar, Dakar, Senegal.,Service d'Immunologie, University Cheikh Anta Diop of Dakar, Dakar, Senegal
| | - Pascal Rihet
- Aix Marseille Univ, INSERM, TAGC, Marseille, France
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32
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Taskent RO, Alioglu ND, Fer E, Melike Donertas H, Somel M, Gokcumen O. Variation and Functional Impact of Neanderthal Ancestry in Western Asia. Genome Biol Evol 2018; 9:3516-3524. [PMID: 29040546 PMCID: PMC5751057 DOI: 10.1093/gbe/evx216] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/12/2017] [Indexed: 12/14/2022] Open
Abstract
Neanderthals contributed genetic material to modern humans via multiple admixture events. Initial admixture events presumably occurred in Western Asia shortly after humans migrated out of Africa. Despite being a focal point of admixture, earlier studies indicate lower Neanderthal introgression rates in some Western Asian populations as compared with other Eurasian populations. To better understand the genome-wide and phenotypic impact of Neanderthal introgression in the region, we sequenced whole genomes of nine present-day Europeans, Africans, and the Western Asian Druze at high depth, and analyzed available whole genome data from various other populations, including 16 genomes from present-day Turkey. Our results confirmed previous observations that contemporary Western Asian populations, on an average, have lower levels of Neanderthal-introgressed DNA relative to other Eurasian populations. Modern Western Asians also show comparatively high variability in Neanderthal ancestry, which may be attributed to the complex demographic history of the region. We further replicated the previously described depletion of putatively functional sequences among Neanderthal-introgressed haplotypes. Still, we find dozens of common Neanderthal-introgressed haplotypes in the Turkish sample associated with human phenotypes, including anthropometric and metabolic traits, as well as the immune response. One of these haplotypes is unusually long and harbors variants that affect the expression of members of the CCR gene family and are associated with celiac disease. Overall, our results paint a complex first picture of the genomic impact of Neanderthal introgression in the Western Asian populations.
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Affiliation(s)
| | | | - Evrim Fer
- Department of Biology, Middle East Technical University, Ankara, Turkey
| | - Handan Melike Donertas
- Department of Biology, Middle East Technical University, Ankara, Turkey.,European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Mehmet Somel
- Department of Biology, Middle East Technical University, Ankara, Turkey
| | - Omer Gokcumen
- Department of Biological Sciences, University at Buffalo
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33
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Patel R, Scheinfeldt LB, Sanderford MD, Lanham TR, Tamura K, Platt A, Glicksberg BS, Xu K, Dudley JT, Kumar S. Adaptive Landscape of Protein Variation in Human Exomes. Mol Biol Evol 2018; 35:2015-2025. [PMID: 29846678 PMCID: PMC6063297 DOI: 10.1093/molbev/msy107] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
The human genome contains hundreds of thousands of missense mutations. However, only a handful of these variants are known to be adaptive, which implies that adaptation through protein sequence change is an extremely rare phenomenon in human evolution. Alternatively, existing methods may lack the power to pinpoint adaptive variation. We have developed and applied an Evolutionary Probability Approach (EPA) to discover candidate adaptive polymorphisms (CAPs) through the discordance between allelic evolutionary probabilities and their observed frequencies in human populations. EPA reveals thousands of missense CAPs, which suggest that a large number of previously optimal alleles experienced a reversal of fortune in the human lineage. We explored nonadaptive mechanisms to explain CAPs, including the effects of demography, mutation rate variability, and negative and positive selective pressures in modern humans. Many nonadaptive hypotheses were tested, but failed to explain the data, which suggests that a large proportion of CAP alleles have increased in frequency due to beneficial selection. This suggestion is supported by the fact that a vast majority of adaptive missense variants discovered previously in humans are CAPs, and hundreds of CAP alleles are protective in genotype-phenotype association data. Our integrated phylogenomic and population genetic EPA approach predicts the existence of thousands of nonneutral candidate variants in the human proteome. We expect this collection to be enriched in beneficial variation. The EPA approach can be applied to discover candidate adaptive variation in any protein, population, or species for which allele frequency data and reliable multispecies alignments are available.
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Affiliation(s)
- Ravi Patel
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
- Department of Biology, Temple University, Philadelphia, PA
| | - Laura B Scheinfeldt
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
- Department of Biology, Temple University, Philadelphia, PA
- Coriell Institute for Medical Research, Camden, NJ
| | - Maxwell D Sanderford
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
| | - Tamera R Lanham
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
| | - Koichiro Tamura
- Department of Biology, Tokyo Metropolitan University, Tokyo, Japan
| | - Alexander Platt
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
- Department of Biology, Temple University, Philadelphia, PA
- Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA
| | - Benjamin S Glicksberg
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ke Xu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Joel T Dudley
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA
- Department of Biology, Temple University, Philadelphia, PA
- Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah, Saudi Arabia
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34
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Genetic analysis of cerebral malaria in the mouse model infected with Plasmodium berghei. Mamm Genome 2018; 29:488-506. [DOI: 10.1007/s00335-018-9752-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2018] [Accepted: 06/05/2018] [Indexed: 12/22/2022]
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Rivas MA, Avila BE, Koskela J, Huang H, Stevens C, Pirinen M, Haritunians T, Neale BM, Kurki M, Ganna A, Graham D, Glaser B, Peter I, Atzmon G, Barzilai N, Levine AP, Schiff E, Pontikos N, Weisburd B, Lek M, Karczewski KJ, Bloom J, Minikel EV, Petersen BS, Beaugerie L, Seksik P, Cosnes J, Schreiber S, Bokemeyer B, Bethge J, Heap G, Ahmad T, Plagnol V, Segal AW, Targan S, Turner D, Saavalainen P, Farkkila M, Kontula K, Palotie A, Brant SR, Duerr RH, Silverberg MS, Rioux JD, Weersma RK, Franke A, Jostins L, Anderson CA, Barrett JC, MacArthur DG, Jalas C, Sokol H, Xavier RJ, Pulver A, Cho JH, McGovern DPB, Daly MJ. Insights into the genetic epidemiology of Crohn's and rare diseases in the Ashkenazi Jewish population. PLoS Genet 2018; 14:e1007329. [PMID: 29795570 PMCID: PMC5967709 DOI: 10.1371/journal.pgen.1007329] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Accepted: 03/22/2018] [Indexed: 02/05/2023] Open
Abstract
As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p<10-16). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC (sites VCF available via FTP at ftp.broadinstitute.org/pub/ExAC_release/release0.3/) to pinpoint genetic variation that contributes to variable disease predisposition across populations.
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Affiliation(s)
- Manuel A. Rivas
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Department of Biomedical Data Science, Stanford University, Stanford, CA, United States of America
| | - Brandon E. Avila
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Jukka Koskela
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Hailiang Huang
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Christine Stevens
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Talin Haritunians
- Translational Genomics Unit, F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
| | - Benjamin M. Neale
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Mitja Kurki
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Andrea Ganna
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Daniel Graham
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
| | - Benjamin Glaser
- Hadassah-Hebrew University Medical Center, Endocrinology and Metabolism Service Department of Internal Medicine, Jerusalem, Israel
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Gil Atzmon
- Department of Genetics and Medicine, Albert Einstein College of Medicine, Bronx, NY, United States of America
- Faculty of Natural Sciences, University of Haifa, Haifa, Israel
| | - Nir Barzilai
- Department of Genetics and Medicine, Albert Einstein College of Medicine, Bronx, NY, United States of America
| | - Adam P. Levine
- Division of Medicine, University College London, London, United Kingdom
| | - Elena Schiff
- Division of Medicine, University College London, London, United Kingdom
| | - Nikolas Pontikos
- Division of Medicine, University College London, London, United Kingdom
- UCL Genetics Institute, University College London, London, United Kingdom
| | - Ben Weisburd
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Monkol Lek
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Konrad J. Karczewski
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Jonathan Bloom
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Eric V. Minikel
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Britt-Sabina Petersen
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Laurent Beaugerie
- Gastroenterology Department, Saint-Antoine Hospital, AP-HP, UPMC Univ Paris, Paris, France
| | - Philippe Seksik
- Gastroenterology Department, Saint-Antoine Hospital, AP-HP, UPMC Univ Paris, Paris, France
| | - Jacques Cosnes
- Gastroenterology Department, Saint-Antoine Hospital, AP-HP, UPMC Univ Paris, Paris, France
| | - Stefan Schreiber
- Department of Internal Medicine, University Hospital Schleswig-Holstein, Kiel, Germany
| | | | - Johannes Bethge
- Department of Internal Medicine, University Hospital Schleswig-Holstein, Kiel, Germany
| | | | | | | | - Graham Heap
- IBD Pharmacogenetics, Royal Devon and Exeter NHS Trust, Exeter, United Kingdom
| | - Tariq Ahmad
- Peninsula College of Medicine and Dentistry, Exeter, United Kingdom
| | - Vincent Plagnol
- UCL Genetics Institute, University College London, London, United Kingdom
| | - Anthony W. Segal
- Division of Medicine, University College London, London, United Kingdom
| | - Stephan Targan
- Translational Genomics Unit, F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
| | - Dan Turner
- Juliet Keidan Institute of Pediatric Gastroenterology and Nutrition, Shaare Zedek Medical Center, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Paivi Saavalainen
- Research Programs Unit, Immunobiology, and Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland
| | - Martti Farkkila
- Department of Medicine, Division of Gastroenterology, Helsinki University Hospital, Helsinki, Finland
| | - Kimmo Kontula
- Department of Medicine, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Aarno Palotie
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States of America
| | - Steven R. Brant
- Meyerhoff Inflammatory Bowel Disease Center, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, United States of America
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States of America
| | - Richard H. Duerr
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States of America
- Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, United States of America
| | - Mark S. Silverberg
- Inflammatory Bowel Disease Centre, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - John D. Rioux
- Research Center, Montreal Heart Institute, Montréal, Québec, Canada
- Department of Medicine, Université de Montréal, Montréal, Québec, Canada
| | - Rinse K. Weersma
- Department of Gastroenterology and Hepatology, University Medical Center Groningen, Groningen, The Netherlands
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Luke Jostins
- Wellcome Trust Centre for Human Genetics, Oxford University, Oxford, United Kingdom
| | - Carl A. Anderson
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - Jeffrey C. Barrett
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, United Kingdom
| | - Daniel G. MacArthur
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
| | - Chaim Jalas
- Bonei Olam, Center for Rare Jewish Genetic Disorders, Brooklyn, NY, United States of America
| | - Harry Sokol
- Gastroenterology Department, Saint-Antoine Hospital, AP-HP, UPMC Univ Paris, Paris, France
| | - Ramnik J. Xavier
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Gastrointestinal Unit and Center for the Study of Inflammatory Bowel Disease and Center for Computational and Integrative Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States of America
| | - Ann Pulver
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America
| | - Judy H. Cho
- Icahn School of Medicine at Mount Sinai, Dr Henry D. Janowitz Division of Gastroenterology, New York, NY, United States of America
| | - Dermot P. B. McGovern
- Translational Genomics Unit, F. Widjaja Foundation Inflammatory Bowel and Immunobiology Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
| | - Mark J. Daly
- Medical and Population Genetics, Broad Institute, Cambridge, MA, United States of America
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, United States of America
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
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36
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Opi DH, Swann O, Macharia A, Uyoga S, Band G, Ndila CM, Harrison EM, Thera MA, Kone AK, Diallo DA, Doumbo OK, Lyke KE, Plowe CV, Moulds JM, Shebbe M, Mturi N, Peshu N, Maitland K, Raza A, Kwiatkowski DP, Rockett KA, Williams TN, Rowe JA. Two complement receptor one alleles have opposing associations with cerebral malaria and interact with α +thalassaemia. eLife 2018; 7:e31579. [PMID: 29690995 PMCID: PMC5953541 DOI: 10.7554/elife.31579] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2017] [Accepted: 04/01/2018] [Indexed: 12/13/2022] Open
Abstract
Malaria has been a major driving force in the evolution of the human genome. In sub-Saharan African populations, two neighbouring polymorphisms in the Complement Receptor One (CR1) gene, named Sl2 and McCb, occur at high frequencies, consistent with selection by malaria. Previous studies have been inconclusive. Using a large case-control study of severe malaria in Kenyan children and statistical models adjusted for confounders, we estimate the relationship between Sl2 and McCb and malaria phenotypes, and find they have opposing associations. The Sl2 polymorphism is associated with markedly reduced odds of cerebral malaria and death, while the McCb polymorphism is associated with increased odds of cerebral malaria. We also identify an apparent interaction between Sl2 and α+thalassaemia, with the protective association of Sl2 greatest in children with normal α-globin. The complex relationship between these three mutations may explain previous conflicting findings, highlighting the importance of considering genetic interactions in disease-association studies.
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Affiliation(s)
- D Herbert Opi
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
- Centre for Immunity, Infection and Evolution, Institute of Immunology and Infection Research, School of Biological SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Olivia Swann
- Centre for Immunity, Infection and Evolution, Institute of Immunology and Infection Research, School of Biological SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Alexander Macharia
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
| | - Sophie Uyoga
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
| | - Gavin Band
- Wellcome Trust Centre for Human GeneticsUniversity of OxfordOxfordUnited Kingdom
| | - Carolyne M Ndila
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
| | - Ewen M Harrison
- Centre for Medical InfomaticsUsher Insitute of Population Health Sciences and Informatics, University of EdinburghEdinburghUnited Kingdom
| | - Mahamadou A Thera
- Malaria Research and Training Centre, Faculty of Medicine, Pharmacy, and DentistryUniversity of BamakoBamakoMali
| | - Abdoulaye K Kone
- Malaria Research and Training Centre, Faculty of Medicine, Pharmacy, and DentistryUniversity of BamakoBamakoMali
| | - Dapa A Diallo
- Malaria Research and Training Centre, Faculty of Medicine, Pharmacy, and DentistryUniversity of BamakoBamakoMali
| | - Ogobara K Doumbo
- Malaria Research and Training Centre, Faculty of Medicine, Pharmacy, and DentistryUniversity of BamakoBamakoMali
| | - Kirsten E Lyke
- Division of Malaria Research, Institute for Global HealthUniversity of Maryland School of MedicineBaltimoreUnited States
| | - Christopher V Plowe
- Division of Malaria Research, Institute for Global HealthUniversity of Maryland School of MedicineBaltimoreUnited States
| | | | - Mohammed Shebbe
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
| | - Neema Mturi
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
| | - Norbert Peshu
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
| | - Kathryn Maitland
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
- Department of MedicineImperial CollegeLondonUnited Kingdom
| | - Ahmed Raza
- Centre for Immunity, Infection and Evolution, Institute of Immunology and Infection Research, School of Biological SciencesUniversity of EdinburghEdinburghUnited Kingdom
| | - Dominic P Kwiatkowski
- Wellcome Trust Centre for Human GeneticsUniversity of OxfordOxfordUnited Kingdom
- Wellcome Trust Sanger InstituteCambridgeUnited Kingdom
| | - Kirk A Rockett
- Wellcome Trust Centre for Human GeneticsUniversity of OxfordOxfordUnited Kingdom
| | - Thomas N Williams
- Kenya Medical Research Institute-Wellcome Trust Research ProgrammeKilifiKenya
- Department of MedicineImperial CollegeLondonUnited Kingdom
| | - J Alexandra Rowe
- Centre for Immunity, Infection and Evolution, Institute of Immunology and Infection Research, School of Biological SciencesUniversity of EdinburghEdinburghUnited Kingdom
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37
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Liu YH, Wang L, Xu T, Guo X, Li Y, Yin TT, Yang HC, Hu Y, Adeola AC, Sanke OJ, Otecko NO, Wang M, Ma Y, Charles OS, Sinding MHS, Gopalakrishnan S, Alfredo Samaniego J, Hansen AJ, Fernandes C, Gaubert P, Budd J, Dawuda PM, Knispel Rueness E, Jiang L, Zhai W, Gilbert MTP, Peng MS, Qi X, Wang GD, Zhang YP. Whole-Genome Sequencing of African Dogs Provides Insights into Adaptations against Tropical Parasites. Mol Biol Evol 2017; 35:287-298. [DOI: 10.1093/molbev/msx258] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
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Mozzi A, Pontremoli C, Sironi M. Genetic susceptibility to infectious diseases: Current status and future perspectives from genome-wide approaches. INFECTION GENETICS AND EVOLUTION 2017; 66:286-307. [PMID: 28951201 PMCID: PMC7106304 DOI: 10.1016/j.meegid.2017.09.028] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Revised: 09/20/2017] [Accepted: 09/21/2017] [Indexed: 02/06/2023]
Abstract
Genome-wide association studies (GWASs) have been widely applied to identify genetic factors that affect complex diseases or traits. Presently, the GWAS Catalog includes > 2800 human studies. Of these, only a minority have investigated the susceptibility to infectious diseases or the response to therapies for the treatment or prevention of infections. Despite their limited application in the field, GWASs have provided valuable insights by pinpointing associations to both innate and adaptive immune response loci, as well as novel unexpected risk factors for infection susceptibility. Herein, we discuss some issues and caveats of GWASs for infectious diseases, we review the most recent findings ensuing from these studies, and we provide a brief summary of selected GWASs for infections in non-human mammals. We conclude that, although the general trend in the field of complex traits is to shift from GWAS to next-generation sequencing, important knowledge on infectious disease-related traits can be still gained by GWASs, especially for those conditions that have never been investigated using this approach. We suggest that future studies will benefit from the leveraging of information from the host's and pathogen's genomes, as well as from the exploration of models that incorporate heterogeneity across populations and phenotypes. Interactions within HLA genes or among HLA variants and polymorphisms located outside the major histocompatibility complex may also play an important role in shaping the susceptibility and response to invading pathogens. Relatively few GWASs for infectious diseases were performed. Phenotype heterogeneity and case/control misclassification can affect GWAS power. Adaptive and innate immunity loci were identified in several infectious disease GWASs. Unexpected loci (e.g., lncRNAs) were also associated with infection susceptibility. GWASs should integrate host and pathogen diversity and use complex association models.
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Affiliation(s)
- Alessandra Mozzi
- Bioinformatics, Scientific Institute IRCCS E.MEDEA, 23842 Bosisio Parini, Italy
| | - Chiara Pontremoli
- Bioinformatics, Scientific Institute IRCCS E.MEDEA, 23842 Bosisio Parini, Italy
| | - Manuela Sironi
- Bioinformatics, Scientific Institute IRCCS E.MEDEA, 23842 Bosisio Parini, Italy.
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39
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Human genetic variation in VAC14 regulates Salmonella invasion and typhoid fever through modulation of cholesterol. Proc Natl Acad Sci U S A 2017; 114:E7746-E7755. [PMID: 28827342 DOI: 10.1073/pnas.1706070114] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Risk, severity, and outcome of infection depend on the interplay of pathogen virulence and host susceptibility. Systematic identification of genetic susceptibility to infection is being undertaken through genome-wide association studies, but how to expeditiously move from genetic differences to functional mechanisms is unclear. Here, we use genetic association of molecular, cellular, and human disease traits and experimental validation to demonstrate that genetic variation affects expression of VAC14, a phosphoinositide-regulating protein, to influence susceptibility to Salmonella enterica serovar Typhi (S Typhi) infection. Decreased VAC14 expression increased plasma membrane cholesterol, facilitating Salmonella docking and invasion. This increased susceptibility at the cellular level manifests as increased susceptibility to typhoid fever in a Vietnamese population. Furthermore, treating zebrafish with a cholesterol-lowering agent, ezetimibe, reduced susceptibility to S Typhi. Thus, coupling multiple genetic association studies with mechanistic dissection revealed how VAC14 regulates Salmonella invasion and typhoid fever susceptibility and may open doors to new prophylactic/therapeutic approaches.
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40
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Diversity and inclusion in genomic research: why the uneven progress? J Community Genet 2017; 8:255-266. [PMID: 28770442 PMCID: PMC5614884 DOI: 10.1007/s12687-017-0316-6] [Citation(s) in RCA: 170] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 06/29/2017] [Indexed: 12/15/2022] Open
Abstract
Conducting genomic research in diverse populations has led to numerous advances in our understanding of human history, biology, and health disparities, in addition to discoveries of vital clinical significance. Conducting genomic research in diverse populations is also important in ensuring that the genomic revolution does not exacerbate health disparities by facilitating discoveries that will disproportionately benefit well-represented populations. Despite the general agreement on the need for genomic research in diverse populations in terms of equity and scientific progress, genomic research remains largely focused on populations of European descent. In this article, we describe the rationale for conducting genomic research in diverse populations by reviewing examples of advances facilitated by their inclusion. We also explore some of the factors that perpetuate the disproportionate attention on well-represented populations. Finally, we discuss ongoing efforts to ameliorate this continuing bias. Collaborative and intensive efforts at all levels of research, from the funding of studies to the publication of their findings, will be necessary to ensure that genomic research does not conserve historical inequalities or curtail the contribution that genomics could make to the health of all humanity.
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41
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Langlais D, Fodil N, Gros P. Genetics of Infectious and Inflammatory Diseases: Overlapping Discoveries from Association and Exome-Sequencing Studies. Annu Rev Immunol 2017; 35:1-30. [DOI: 10.1146/annurev-immunol-051116-052442] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- David Langlais
- McGill University Research Centre on Complex Traits, McGill University, Montreal, Quebec H3G 0B1, Canada;, ,
- Department of Biochemistry, McGill University, Montreal, Quebec H3G 0B1, Canada
| | - Nassima Fodil
- McGill University Research Centre on Complex Traits, McGill University, Montreal, Quebec H3G 0B1, Canada;, ,
- Department of Biochemistry, McGill University, Montreal, Quebec H3G 0B1, Canada
| | - Philippe Gros
- McGill University Research Centre on Complex Traits, McGill University, Montreal, Quebec H3G 0B1, Canada;, ,
- Department of Biochemistry, McGill University, Montreal, Quebec H3G 0B1, Canada
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42
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Lack of Association of CD55 Receptor Genetic Variants and Severe Malaria in Ghanaian Children. G3-GENES GENOMES GENETICS 2017; 7:859-864. [PMID: 28104671 PMCID: PMC5345716 DOI: 10.1534/g3.116.036475] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
In a recent report, the cellular receptor CD55 was identified as a molecule essential for the invasion of human erythrocytes by Plasmodium falciparum, the causal agent of the most severe form of malaria. As this invasion process represents a critical step during infection with the parasite, it was hypothesized that genetic variants in the gene could affect severe malaria (SM) susceptibility. We performed high-resolution variant discovery of rare and common genetic variants in the human CD55 gene. Association testing of these variants in over 1700 SM cases and unaffected control individuals from the malaria-endemic Ashanti Region in Ghana, West Africa, were performed on the basis of single variants, combined rare variant analyses, and reconstructed haplotypes. A total of 26 genetic variants were detected in coding and regulatory regions of CD55. Five variants were previously unknown. None of the single variants, rare variants, or haplotypes showed evidence for association with SM or P. falciparum density. Here, we present the first comprehensive analysis of variation in the CD55 gene in the context of SM and show that genetic variants present in a Ghanaian study group appear not to influence susceptibility to the disease.
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43
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Nguyen TTP, Le VS, Ho HB, Si Le Q. Building Ancestral Recombination Graphs for Whole Genomes. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2017; 14:478-483. [PMID: 26992176 DOI: 10.1109/tcbb.2016.2542801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
We propose a heuristic algorithm, called ARG4WG, to build plausible ancestral recombination graphs (ARGs) from thousands of whole genome samples. By using the longest shared end for recombination inference, ARG4WG constructs ARGs with small numbers of recombination events that perform well in association mapping on genome-wide association studies.
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44
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Reilly JP, Meyer NJ, Christie JD. Genetics in the Prevention and Treatment of Sepsis. SEPSIS 2017. [DOI: 10.1007/978-3-319-48470-9_15] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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45
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Frequency of TNFA, INFG, and IL10 Gene Polymorphisms and Their Association with Malaria Vivax and Genomic Ancestry. Mediators Inflamm 2016; 2016:5168363. [PMID: 27999453 PMCID: PMC5143728 DOI: 10.1155/2016/5168363] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Revised: 07/14/2016] [Accepted: 09/27/2016] [Indexed: 02/08/2023] Open
Abstract
Polymorphisms in cytokine genes can alter the production of these proteins and consequently affect the immune response. The trihybrid heterogeneity of the Brazilian population is characterized as a condition for the use of ancestry informative markers. The objective of this study was to evaluate the frequency of -1031T>C, -308G>A and -238G>A TNFA, +874 A>T IFNG and -819C>T, and -592C>A IL10 gene polymorphisms and their association with malaria vivax and genomic ancestry. Samples from 90 vivax malaria-infected individuals and 51 noninfected individuals from northern Brazil were evaluated. Genotyping was carried out by using ASO-PCR or PCR/RFLP. The genomic ancestry of the individuals was classified using 48 insertion/deletion polymorphism biallelic markers. There were no differences in the proportions of African, European, and Native American ancestry between men and women. No significant association was observed for the allele and genotype frequencies of the 6 SNPs between malaria-infected and noninfected individuals. However, there was a trend toward decreasing the frequency of individuals carrying the TNF-308A allele with the increasing proportion of European ancestry. No ethnic-specific SNPs were identified, and there was no allelic or genotype association with susceptibility or resistance to vivax malaria. Understanding the genomic mechanisms by which ancestry influences this association is critical and requires further study.
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46
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Sun W, Kechris K, Jacobson S, Drummond MB, Hawkins GA, Yang J, Chen TH, Quibrera PM, Anderson W, Barr RG, Basta PV, Bleecker ER, Beaty T, Casaburi R, Castaldi P, Cho MH, Comellas A, Crapo JD, Criner G, Demeo D, Christenson SA, Couper DJ, Curtis JL, Doerschuk CM, Freeman CM, Gouskova NA, Han MK, Hanania NA, Hansel NN, Hersh CP, Hoffman EA, Kaner RJ, Kanner RE, Kleerup EC, Lutz S, Martinez FJ, Meyers DA, Peters SP, Regan EA, Rennard SI, Scholand MB, Silverman EK, Woodruff PG, O’Neal WK, Bowler RP. Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD. PLoS Genet 2016; 12:e1006011. [PMID: 27532455 PMCID: PMC4988780 DOI: 10.1371/journal.pgen.1006011] [Citation(s) in RCA: 71] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Accepted: 04/05/2016] [Indexed: 12/20/2022] Open
Abstract
Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p < 8 X 10-10) pQTLs in 38 (43%) of blood proteins tested. Most pQTL SNPs were novel with low overlap to eQTL SNPs. The pQTL SNPs explained >10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10-392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group.
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Affiliation(s)
- Wei Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Sean Jacobson
- National Jewish Health, Denver, Colorado, United States of America
| | - M. Bradley Drummond
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Gregory A. Hawkins
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Jenny Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ting-huei Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Pedro Miguel Quibrera
- Collaborative Studies Coordinating Center, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Wayne Anderson
- Marsico Lung Institute/Cystic Fibrosis Research Center, Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina United States of America
| | - R. Graham Barr
- Department of Medicine, Columbia University Medical Center, New York, New York; Department of Epidemiology, Mailman School of Public Health at Columbia University, New York, New York, United States of America
| | - Patricia V. Basta
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Eugene R. Bleecker
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Terri Beaty
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University,Baltimore, Maryland, United States of America
| | - Richard Casaburi
- Division of Respiratory and Critical Care Physiology and Medicine, Harbor- University of California at Los Angeles Medical Center, Torrance, California, United States of America
| | - Peter Castaldi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Michael H. Cho
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Alejandro Comellas
- Division of Pulmonary and Critical Care Medicine, University of Iowa, Iowa City, Iowa, United States of America
| | - James D. Crapo
- Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, National Jewish Health, Denver, Colorado, United States of America
| | - Gerard Criner
- Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania, United States of America
| | - Dawn Demeo
- Division of Pulmonary and Critical Care Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Stephanie A. Christenson
- Division of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of San Francisco Medical Center, University of California San Francisco, San Francisco, California, United States of America
| | - David J. Couper
- Collaborative Studies Coordinating Center, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Jeffrey L. Curtis
- Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, Michigan; VA Ann Arbor Healthcare System, Ann Arbor, Michigan, United States of America
| | - Claire M. Doerschuk
- Marsico Lung Institute/Cystic Fibrosis Research Center, Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina United States of America
| | - Christine M. Freeman
- Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, Michigan; VA Ann Arbor Healthcare System, Ann Arbor, Michigan, United States of America
| | - Natalia A. Gouskova
- Collaborative Studies Coordinating Center, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - MeiLan K. Han
- Division of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, Michigan, United States of America
| | - Nicola A. Hanania
- Section of Pulmonary and Critical Care Medicine, Baylor College of Medicine, Houston, Texas, United States of America
| | - Nadia N. Hansel
- Division of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Craig P. Hersh
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Eric A. Hoffman
- Department of Radiology, Division of Physiologic Imaging, University of Iowa Hospitals and Clinics, Iowa City, Iowa, United States of America
| | - Robert J. Kaner
- Department of Genetic Medicine, Weill Cornell Medical College, New York, New York, Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medical College, New York, New York, United States of America
| | - Richard E. Kanner
- Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Utah, Salt Lake City, Utah, United States of America
| | - Eric C. Kleerup
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, United States of America
| | - Sharon Lutz
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America
| | - Fernando J. Martinez
- Department of Medicine, Weill Cornell Medical College, New York-Presbyterian Hospital/Weill Cornell Medical Center, New York, New York, United States of America
| | - Deborah A. Meyers
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Stephen P. Peters
- Department of Medicine, Division of Pulmonary, Critical Care, Allergy and Immunologic Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, United States of America
| | - Elizabeth A. Regan
- Department of Medicine, National Jewish Health, Denver, Colorado United States of America
| | - Stephen I. Rennard
- Division of Pulmonary and Critical Care Medicine, University of Nebraska, Omaha, Nebraska, United States of America
| | - Mary Beth Scholand
- Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Utah, Salt Lake City, Utah, United States of America
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Prescott G. Woodruff
- Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine and Cardiovascular Research Institute, University of California San Francisco School of Medicine, San Francisco, California, United States of America
| | - Wanda K. O’Neal
- Marsico Lung Institute/Cystic Fibrosis Research Center, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina United States of America
| | - Russell P. Bowler
- Department of Medicine, Division of Pulmonary Medicine, National Jewish Health, Denver, Colorado, United States of America
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Lu Q, Aguilar BJ, Li M, Jiang Y, Chen YH. Genetic alterations of δ-catenin/NPRAP/Neurojungin (CTNND2): functional implications in complex human diseases. Hum Genet 2016; 135:1107-16. [PMID: 27380241 PMCID: PMC5021578 DOI: 10.1007/s00439-016-1705-3] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Accepted: 06/23/2016] [Indexed: 02/07/2023]
Abstract
Some genes involved in complex human diseases are particularly vulnerable to genetic variations such as single nucleotide polymorphism, copy number variations, and mutations. For example, Ras mutations account for over 30 % of all human cancers. Additionally, there are some genes that can display different variations with functional impact in different diseases that are unrelated. One such gene stands out: δ-catenin/NPRAP/Neurojungin with gene designation as CTNND2 on chromosome 5p15.2. Recent advances in genome wide association as well as molecular biology approaches have uncovered striking involvement of δ-catenin gene variations linked to complex human disorders. These disorders include cancer, bipolar disorder, schizophrenia, autism, Cri-du-chat syndrome, myopia, cortical cataract-linked Alzheimer's disease, and infectious diseases. This list has rapidly grown longer in recent years, underscoring the pivotal roles of δ-catenin in critical human diseases. δ-Catenin is an adhesive junction-associated protein in the delta subfamily of the β-catenin superfamily. δ-Catenin functions in Wnt signaling to regulate gene expression and modulate Rho GTPases of the Ras superfamily in cytoskeletal reorganization. δ-Catenin likely lies where Wnt signaling meets Rho GTPases and is a unique and vulnerable common target for mutagenesis in different human diseases.
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Affiliation(s)
- Qun Lu
- Department of Anatomy and Cell Biology, Brody School of Medicine at East Carolina University, Greenville, NC, 27834, USA. .,The Harriet and John Wooten Laboratory for Alzheimer's and Neurodegenerative Diseases Research, Brody School of Medicine at East Carolina University, Greenville, NC, 27834, USA. .,Department of Urological Surgery, Capital Medical University Affiliated Beijing Anzhen Hospital, Beijing, 100029, China.
| | - Byron J Aguilar
- Department of Anatomy and Cell Biology, Brody School of Medicine at East Carolina University, Greenville, NC, 27834, USA
| | - Mingchuan Li
- Department of Anatomy and Cell Biology, Brody School of Medicine at East Carolina University, Greenville, NC, 27834, USA.,Department of Urological Surgery, Capital Medical University Affiliated Beijing Anzhen Hospital, Beijing, 100029, China
| | - Yongguang Jiang
- Department of Urological Surgery, Capital Medical University Affiliated Beijing Anzhen Hospital, Beijing, 100029, China
| | - Yan-Hua Chen
- Department of Anatomy and Cell Biology, Brody School of Medicine at East Carolina University, Greenville, NC, 27834, USA.,Department of Pediatrics, Brody School of Medicine at East Carolina University, Greenville, NC, 27834, USA
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49
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Busby GB, Band G, Si Le Q, Jallow M, Bougama E, Mangano VD, Amenga-Etego LN, Enimil A, Apinjoh T, Ndila CM, Manjurano A, Nyirongo V, Doumba O, Rockett KA, Kwiatkowski DP, Spencer CC. Admixture into and within sub-Saharan Africa. eLife 2016; 5. [PMID: 27324836 PMCID: PMC4915815 DOI: 10.7554/elife.15266] [Citation(s) in RCA: 87] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2016] [Accepted: 05/17/2016] [Indexed: 12/27/2022] Open
Abstract
Similarity between two individuals in the combination of genetic markers along their chromosomes indicates shared ancestry and can be used to identify historical connections between different population groups due to admixture. We use a genome-wide, haplotype-based, analysis to characterise the structure of genetic diversity and gene-flow in a collection of 48 sub-Saharan African groups. We show that coastal populations experienced an influx of Eurasian haplotypes over the last 7000 years, and that Eastern and Southern Niger-Congo speaking groups share ancestry with Central West Africans as a result of recent population expansions. In fact, most sub-Saharan populations share ancestry with groups from outside of their current geographic region as a result of gene-flow within the last 4000 years. Our in-depth analysis provides insight into haplotype sharing across different ethno-linguistic groups and the recent movement of alleles into new environments, both of which are relevant to studies of genetic epidemiology. DOI:http://dx.doi.org/10.7554/eLife.15266.001 Our genomes contain a record of historical events. This is because when groups of people are separated for generations, the DNA sequence in the two groups’ genomes will change in different ways. Looking at the differences in the genomes of people from the same population can help researchers to understand and reconstruct the historical interactions that brought their ancestors together. The mixing of two populations that were previously separate is known as admixture. Africa as a continent has few written records of its history. This means that it is somewhat unknown which important movements of people in the past generated the populations found in modern-day Africa. Busby et al. have now attempted to use DNA to look into this and reconstruct the last 4000 years of genetic history in African populations. As has been shown in other regions of the world, the new analysis showed that all African populations are the result of historical admixture events. However, Busby et al. could characterize these events to unprecedented level of detail. For example, multiple ethnic groups from The Gambia and Mali all show signs of sharing the same set of ancestors from West Africa, Europe and Asia who mixed around 2000 years ago. Evidence of a migration of people from Central West Africa, known as the Bantu expansion, could also be detected, and was shown to carry genes to the south and east. An important next step will be to now look at the consequences of the observed gene-flow, and ask if it has contributed to spreading beneficial, or detrimental, mutations around Africa. DOI:http://dx.doi.org/10.7554/eLife.15266.002
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Affiliation(s)
- George Bj Busby
- Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom
| | - Gavin Band
- Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom.,Wellcome Trust Sanger Institute, Cambridge, United Kingdom
| | - Quang Si Le
- Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom
| | - Muminatou Jallow
- Medical Research Council Unit, Serrekunda, The Gambia.,Royal Victoria Teaching Hospital, Banjul, The Gambia
| | - Edith Bougama
- Centre National de Recherche et de Formation sur le Paludisme, Ouagadougou, Burkina Faso
| | - Valentina D Mangano
- Dipartimento di Sanita Publica e Malattie Infettive, University of Rome La Sapienza, Rome, Italy
| | | | | | - Tobias Apinjoh
- Department of Biochemistry and Molecular Biology, University of Buea, Buea, Cameroon
| | | | - Alphaxard Manjurano
- Joint Malaria Programme, Kilimanjaro Christian Medical College, Moshi, Tanzania.,Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Vysaul Nyirongo
- Malawi-Liverpool Wellcome Trust Clinical Research Programme, College of Medicine, University of Malawi, Blantyre, Malawi
| | - Ogobara Doumba
- Malaria Research and Training Centre, University of Bamako, Bamako, Mali
| | - Kirk A Rockett
- Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom.,Wellcome Trust Sanger Institute, Cambridge, United Kingdom
| | - Dominic P Kwiatkowski
- Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom.,Wellcome Trust Sanger Institute, Cambridge, United Kingdom
| | - Chris Ca Spencer
- Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom
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Polymorphism in a lincRNA Associates with a Doubled Risk of Pneumococcal Bacteremia in Kenyan Children. Am J Hum Genet 2016; 98:1092-1100. [PMID: 27236921 PMCID: PMC4908194 DOI: 10.1016/j.ajhg.2016.03.025] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Accepted: 03/28/2016] [Indexed: 12/31/2022] Open
Abstract
Bacteremia (bacterial bloodstream infection) is a major cause of illness and death in sub-Saharan Africa but little is known about the role of human genetics in susceptibility. We conducted a genome-wide association study of bacteremia susceptibility in more than 5,000 Kenyan children as part of the Wellcome Trust Case Control Consortium 2 (WTCCC2). Both the blood-culture-proven bacteremia case subjects and healthy infants as controls were recruited from Kilifi, on the east coast of Kenya. Streptococcus pneumoniae is the most common cause of bacteremia in Kilifi and was thus the focus of this study. We identified an association between polymorphisms in a long intergenic non-coding RNA (lincRNA) gene (AC011288.2) and pneumococcal bacteremia and replicated the results in the same population (p combined = 1.69 × 10(-9); OR = 2.47, 95% CI = 1.84-3.31). The susceptibility allele is African specific, derived rather than ancestral, and occurs at low frequency (2.7% in control subjects and 6.4% in case subjects). Our further studies showed AC011288.2 expression only in neutrophils, a cell type that is known to play a major role in pneumococcal clearance. Identification of this novel association will further focus research on the role of lincRNAs in human infectious disease.
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