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Featured researches published by Kenneth Ekoru.


PLOS Genetics | 2014

A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness

Jared O'Connell; Deepti Gurdasani; Olivier Delaneau; Nicola Pirastu; Sheila Ulivi; Massimiliano Cocca; Michela Traglia; Jie Huang; Jennifer E. Huffman; Igor Rudan; Ruth McQuillan; Ross M. Fraser; Harry Campbell; Ozren Polasek; Gershim Asiki; Kenneth Ekoru; Caroline Hayward; Alan F. Wright; Veronique Vitart; Pau Navarro; Jean-François Zagury; James F. Wilson; Daniela Toniolo; Paolo Gasparini; Nicole Soranzo; Manjinder S. Sandhu; Jonathan Marchini

Many existing cohorts contain a range of relatedness between genotyped individuals, either by design or by chance. Haplotype estimation in such cohorts is a central step in many downstream analyses. Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations, we have investigated the performance of different phasing methods designed for nominally ‘unrelated’ individuals. We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods, including those designed specifically for isolated populations. In particular, when large amounts of IBD sharing is present, SHAPEIT2 infers close to perfect haplotypes. Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals. First SHAPEIT2 is run ignoring all explicit family information. We then apply a novel HMM method (duoHMM) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome. This allows the correction of switch errors, detection of recombination events and genotyping errors. We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps, and that it infers far fewer spurious recombination events than Merlin. The method can also detect genotyping errors and infer recombination events in otherwise uninformative families, such as trios and duos. The detected recombination events can be used in association scans for recombination phenotypes. The method provides a simple and unified approach to haplotype estimation, that will be of interest to researchers in the fields of human, animal and plant genetics.


International Journal of Epidemiology | 2013

Association of HIV and ART with cardiometabolic traits in sub-Saharan Africa: a systematic review and meta-analysis

David G. Dillon; Deepti Gurdasani; Johanna Riha; Kenneth Ekoru; Gershim Asiki; Billy N. Mayanja; Naomi S. Levitt; Nigel J. Crowther; Moffat Nyirenda; Marina Njelekela; Kaushik Ramaiya; Ousman Nyan; Olanisun Olufemi Adewole; Kathryn Anastos; Livio Azzoni; W. Henry Boom; Caterina Compostella; Joel A. Dave; Halima Dawood; Christian Erikstrup; Carla M.T. Fourie; Henrik Friis; Annamarie Kruger; John Idoko; Chris T. Longenecker; Suzanne Mbondi; Japheth E Mukaya; Eugene Mutimura; Chiratidzo E. Ndhlovu; George PrayGod

Background Sub-Saharan Africa (SSA) has the highest burden of HIV in the world and a rising prevalence of cardiometabolic disease; however, the interrelationship between HIV, antiretroviral therapy (ART) and cardiometabolic traits is not well described in SSA populations. Methods We conducted a systematic review and meta-analysis through MEDLINE and EMBASE (up to January 2012), as well as direct author contact. Eligible studies provided summary or individual-level data on one or more of the following traits in HIV+ and HIV-, or ART+ and ART- subgroups in SSA: body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TGs) and fasting blood glucose (FBG) or glycated hemoglobin (HbA1c). Information was synthesized under a random-effects model and the primary outcomes were the standardized mean differences (SMD) of the specified traits between subgroups of participants. Results Data were obtained from 49 published and 3 unpublished studies which reported on 29 755 individuals. HIV infection was associated with higher TGs [SMD, 0.26; 95% confidence interval (CI), 0.08 to 0.44] and lower HDL (SMD, −0.59; 95% CI, −0.86 to −0.31), BMI (SMD, −0.32; 95% CI, −0.45 to −0.18), SBP (SMD, −0.40; 95% CI, −0.55 to −0.25) and DBP (SMD, −0.34; 95% CI, −0.51 to −0.17). Among HIV+ individuals, ART use was associated with higher LDL (SMD, 0.43; 95% CI, 0.14 to 0.72) and HDL (SMD, 0.39; 95% CI, 0.11 to 0.66), and lower HbA1c (SMD, −0.34; 95% CI, −0.62 to −0.06). Fully adjusted estimates from analyses of individual participant data were consistent with meta-analysis of summary estimates for most traits. Conclusions Broadly consistent with results from populations of European descent, these results suggest differences in cardiometabolic traits between HIV-infected and uninfected individuals in SSA, which might be modified by ART use. In a region with the highest burden of HIV, it will be important to clarify these findings to reliably assess the need for monitoring and managing cardiometabolic risk in HIV-infected populations in SSA.


International Journal of Epidemiology | 2013

Sociodemographic distribution of non-communicable disease risk factors in rural Uganda: a cross-sectional study

Georgina Murphy; Gershim Asiki; Kenneth Ekoru; Rebecca N. Nsubuga; Jessica Nakiyingi-Miiro; Elizabeth H. Young; Janet Seeley; Manjinder S. Sandhu; Anatoli Kamali

BACKGROUND Non-communicable diseases (NCDs) are rapidly becoming leading causes of morbidity and mortality in low- and middle-income countries, including those in sub-Saharan Africa. In contrast to high-income countries, the sociodemographic distribution, including socioeconomic inequalities, of NCDs and their risk factors is unclear in sub-Saharan Africa, particularly among rural populations. METHODS We undertook a cross-sectional population-based survey of 7809 residents aged 13 years or older in the General Population Cohort in south-western rural Uganda. Information on behavioural, physiological and biochemical risk factors was obtained using standardized methods as recommended by the WHO STEPwise Approach to Surveillance. Socioeconomic status (SES) was determined by principal component analysis including household features, ownership, and occupation and education of the head of household. RESULTS SES was found to be associated with NCD risk factors in this rural population. Smoking, alcohol consumption (men only) and low high-density lipoprotein (HDL) cholesterol were more common among those of lower SES. For example, the prevalence of smoking decreased 4-fold from the lowest to the highest SES groups, from 22.0% to 5.7% for men and 2.2% to 0.4% for women, respectively. In contrast, overweight, raised blood pressure, raised HbA1c (women only) and raised cholesterol were more common among those of higher SES. For example, the prevalence of overweight increased 5-fold from 2.1% to 10.1% for men, and 2-fold from 12.0% to 23.4% for women, from the lowest to highest SES groups respectively. However, neither low physical activity nor fruit, vegetable or staples consumption was associated with SES. Furthermore, associations between NCD risk factors and SES were modified by age and sex. CONCLUSIONS Within this rural population, NCD risk factors are common and vary both inversely and positively across the SES gradient. A better understanding of the determinants of the sociodemographic distribution of NCDs and their risk factors in rural sub-Saharan African populations will help identify populations at most risk of developing NCDs and help plan interventions to reduce their burden.


Proceedings of the National Academy of Sciences of the United States of America | 2016

Linear mixed model for heritability estimation that explicitly addresses environmental variation

David Heckerman; Deepti Gurdasani; Carl M. Kadie; Cristina Pomilla; Tommy Carstensen; Hilary C. Martin; Kenneth Ekoru; Rebecca N. Nsubuga; Gerald Ssenyomo; Anatoli Kamali; Pontiano Kaleebu; Christian Widmer; Manjinder S. Sandhu

The linear mixed model (LMM) is now routinely used to estimate heritability. Unfortunately, as we demonstrate, LMM estimates of heritability can be inflated when using a standard model. To help reduce this inflation, we used a more general LMM with two random effects—one based on genomic variants and one based on easily measured spatial location as a proxy for environmental effects. We investigated this approach with simulated data and with data from a Uganda cohort of 4,778 individuals for 34 phenotypes including anthropometric indices, blood factors, glycemic control, blood pressure, lipid tests, and liver function tests. For the genomic random effect, we used identity-by-descent estimates from accurately phased genome-wide data. For the environmental random effect, we constructed a covariance matrix based on a Gaussian radial basis function. Across the simulated and Ugandan data, narrow-sense heritability estimates were lower using the more general model. Thus, our approach addresses, in part, the issue of “missing heritability” in the sense that much of the heritability previously thought to be missing was fictional. Software is available at https://github.com/MicrosoftGenomics/FaST-LMM.


International Journal of Obesity | 2018

Deriving an optimal threshold of waist circumference for detecting cardiometabolic risk in sub-Saharan Africa

Kenneth Ekoru; Georgina Murphy; Elizabeth H. Young; H Delisle; C S Jerome; Felix K. Assah; B Longo–Mbenza; J P D Nzambi; J B K On'Kin; F Buntix; M C Muyer; D L Christensen; C S Wesseh; A Sabir; C Okafor; I D Gezawa; F Puepet; O Enang; T Raimi; E Ohwovoriole; O O Oladapo; Pascal Bovet; Willie Frederick Mollentze; Nigel Unwin; W K Gray; R Walker; K Agoudavi; S Siziya; J Chifamba; Marina Njelekela

Background:Waist circumference (WC) thresholds derived from western populations continue to be used in sub-Saharan Africa (SSA) despite increasing evidence of ethnic variation in the association between adiposity and cardiometabolic disease and availability of data from African populations. We aimed to derive a SSA-specific optimal WC cut-point for identifying individuals at increased cardiometabolic risk.Methods:We used individual level cross-sectional data on 24 181 participants aged ⩾15 years from 17 studies conducted between 1990 and 2014 in eight countries in SSA. Receiver operating characteristic curves were used to derive optimal WC cut-points for detecting the presence of at least two components of metabolic syndrome (MS), excluding WC.Results:The optimal WC cut-point was 81.2 cm (95% CI 78.5–83.8 cm) and 81.0 cm (95% CI 79.2–82.8 cm) for men and women, respectively, with comparable accuracy in men and women. Sensitivity was higher in women (64%, 95% CI 63–65) than in men (53%, 95% CI 51–55), and increased with the prevalence of obesity. Having WC above the derived cut-point was associated with a twofold probability of having at least two components of MS (age-adjusted odds ratio 2.6, 95% CI 2.4–2.9, for men and 2.2, 95% CI 2.0–2.3, for women).Conclusion:The optimal WC cut-point for identifying men at increased cardiometabolic risk is lower (⩾81.2 cm) than current guidelines (⩾94.0 cm) recommend, and similar to that in women in SSA. Prospective studies are needed to confirm these cut-points based on cardiometabolic outcomes.


Global Health, Epidemiology and Genomics | 2017

Whole-genome association study of antibody response to Epstein-Barr virus in an African population: a pilot.

N Sallah; Tommy Carstensen; Katie Wakeham; Rachel Bagni; Nazzarena Labo; Martin Pollard; Deepti Gurdasani; Kenneth Ekoru; Cristina Pomilla; Elizabeth H. Young; Segun Fatumo; Gershim Asiki; Anatoli Kamali; Manjinder S. Sandhu; Paul Kellam; Denise Whitby; Inês Barroso; Robert Newton

Epstein Barr virus (EBV) infects 95% of the global population and is associated with up to 2% of cancers globally. Immunoglobulin G (IgG) antibody levels to EBV have been shown to be heritable and associated with developing malignancies. We, therefore, performed a pilot genome-wide association analysis of anti-EBV IgG traits in an African population, using a combined approach including array genotyping, whole-genome sequencing and imputation to a panel with African sequence data. In 1562 Ugandans, we identify a variant in human leukocyte antigen (HLA)-DQA1, rs9272371 (p = 2.6 × 10−17) associated with anti-EBV nuclear antigen-1 responses. Trans-ancestry meta-analysis and fine-mapping with European-ancestry individuals suggest the presence of distinct HLA class II variants driving associations in Uganda. In addition, we identify four putative, novel, very rare African-specific loci with preliminary evidence for association with anti-viral capsid antigen IgG responses which will require replication for validation. These findings reinforce the need for the expansion of such studies in African populations with relevant datasets to capture genetic diversity.


Global Health, Epidemiology and Genomics | 2016

H3Africa multi-centre study of the prevalence and environmental and genetic determinants of type 2 diabetes in sub-Saharan Africa: study protocol

Kenneth Ekoru; Elizabeth H. Young; Clement Adebamowo; N. Balde; B. J. Hennig; Pontiano Kaleebu; Saidi Kapiga; Naomi S. Levitt; M. Mayige; Jean Claude Mbanya; Mark McCarthy; O. Nyan; Moffat Nyirenda; John Oli; Kaushik Ramaiya; Liam Smeeth; Eugene Sobngwi; Charles N. Rotimi; Manjinder S. Sandhu; Ayesha A. Motala

Summary The burden and aetiology of type 2 diabetes (T2D) and its microvascular complications may be influenced by varying behavioural and lifestyle environments as well as by genetic susceptibility. These aspects of the epidemiology of T2D have not been reliably clarified in sub-Saharan Africa (SSA), highlighting the need for context-specific epidemiological studies with the statistical resolution to inform potential preventative and therapeutic strategies. Therefore, as part of the Human Heredity and Health in Africa (H3Africa) initiative, we designed a multi-site study comprising case collections and population-based surveys at 11 sites in eight countries across SSA. The goal is to recruit up to 6000 T2D participants and 6000 control participants. We will collect questionnaire data, biophysical measurements and biological samples for chronic disease traits, risk factors and genetic data on all study participants. Through integrating epidemiological and genomic techniques, the study provides a framework for assessing the burden, spectrum and environmental and genetic risk factors for T2D and its complications across SSA. With established mechanisms for fieldwork, data and sample collection and management, data-sharing and consent for re-approaching participants, the study will be a resource for future research studies, including longitudinal studies, prospective case ascertainment of incident disease and interventional studies.


African Population Studies | 2010

Mitigating the impact of the epidemic on the households and families of older people in rural Uganda: lessons for social protection

Janet Seeley; Kenneth Ekoru

Using quantitative and qualitative data drawn from a population cohort of 20,000 people in South-West Uganda we explored factors (household size/dependency ratios/ residence patterns/ socio-economic status) which may have exacerbated or eased the impact of the AIDS epidemic for older people (70 years and older). We found that higher socio-economic status, large family size and reciprocal relationships with kin/neighbours were particularly important in shielding older people from the negative effects of AIDS-related deaths among their children; elders without these fared badly. Our findings provide pointers for the targeting of social protection for older people in such resource-constrained settings.


BMC Research Notes | 2013

Patients’ worries before starting antiretroviral therapy and their association with treatment adherence and outcomes: a prospective study in rural Uganda, 2004 - 2009

Billy N. Mayanja; Kenneth Ekoru; Harriet Namugenyi; Rosemary Lubega; Joseph Mugisha


Archive | 2013

NON-COMMUNICABLE DISEASE RISK FACTORS AND MORTALITY Sociodemographic distribution of non-communicable disease risk factors in rural Uganda: a cross-sectional study

Georgina Murphy; Gershim Asiki; Kenneth Ekoru; Rebecca N. Nsubuga; Jessica Nakiyingi-Miiro; Elizabeth H. Young; Janet Seeley; Manjinder S. Sandhu; Anatoli Kamali

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Manjinder S. Sandhu

Wellcome Trust Sanger Institute

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Gershim Asiki

Uganda Virus Research Institute

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Deepti Gurdasani

Wellcome Trust Sanger Institute

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Rebecca N. Nsubuga

Uganda Virus Research Institute

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