Early detection of emerging infectious diseases - implications for vaccine development

Vast quantities of open-source data from news reports, social media and other sources can be harnessed using artificial intelligence and machine learning, and utilised to generate valid early warning signals of emerging epidemics. Early warning signals from open-source data are not a replacement for traditional, validated disease surveillance, but provide a trigger for earlier investigation and diagnostics. This may yield earlier pathogen characterisation and genomic data, which can enable earlier vaccine development or deployment of vaccines. Early warning also provides a more feasible prospect of stamping out epidemics before they spread. There are several of such systems currently, but they are not used widely in public health practice, and only some are publicly available. Routine and widespread use of open-source intelligence, as well as training and capacity building in digital surveillance, will improve pandemic preparedness and early response capability.

Transcriptomics and chromatin accessibility in multiple African population samples

Mapping the functional human genome and impact of genetic variants is often limited to European-descendent population samples. To aid in overcoming this limitation, we measured gene expression using RNA sequencing in lymphoblastoid cell lines (LCLs) from 599 individuals from six African populations to identify novel transcripts including those not represented in the hg38 reference genome. We used whole genomes from the 1000 Genomes Project and 164 Maasai individuals to identify 8,881 expression and 6,949 splicing quantitative trait loci (eQTLs/sQTLs), and 2,611 structural variants associated with gene expression (SV-eQTLs). We further profiled chromatin accessibility using ATAC-Seq in a subset of 100 representative individuals, to identity chromatin accessibility quantitative trait loci (caQTLs) and allele-specific chromatin accessibility, and provide predictions for the functional effect of 78.9 million variants on chromatin accessibility. Using this map of eQTLs and caQTLs we fine-mapped GWAS signals for a range of complex diseases. Combined, this work expands global functional genomic data to identify novel transcripts, functional elements and variants, understand population genetic history of molecular quantitative trait loci, and further resolve the genetic basis of multiple human traits and disease.

Africa-specific human genetic variation near CHD1L associates with HIV-1 load

HIV-1 remains a global health crisis1, highlighting the need to identify new targets for therapies. Here, given the disproportionate HIV-1 burden and marked human genome diversity in Africa2, we assessed the genetic determinants of control of set-point viral load in 3,879 people of African ancestries living with HIV-1 participating in the international collaboration for the genomics of HIV3. We identify a previously undescribed association signal on chromosome 1 where the peak variant associates with an approximately 0.3 log10-transformed copies per ml lower set-point viral load per minor allele copy and is specific to populations of African descent. The top associated variant is intergenic and lies between a long intergenic non-coding RNA (LINC00624) and the coding gene CHD1L, which encodes a helicase that is involved in DNA repair4. Infection assays in iPS cell-derived macrophages and other immortalized cell lines showed increased HIV-1 replication in CHD1L-knockdown and CHD1L-knockout cells. We provide evidence from population genetic studies that Africa-specific genetic variation near CHD1L associates with HIV replication in vivo. Although experimental studies suggest that CHD1L is able to limit HIV infection in some cell types in vitro, further investigation is required to understand the mechanisms underlying our observations, including any potential indirect effects of CHD1L on HIV spread in vivo that our cell-based assays cannot recapitulate.

Hospital admissions linked to SARS-CoV-2 infection in children and adolescents: cohort study of 3.2 million first ascertained infections in England

OBJECTIVE

To describe hospital admissions associated with SARS-CoV-2 infection in children and adolescents.

DESIGN

Cohort study of 3.2 million first ascertained SARS-CoV-2 infections using electronic health care record data.

SETTING

England, July 2020 to February 2022.

PARTICIPANTS

About 12 million children and adolescents (age <18 years) who were resident in England.

MAIN OUTCOME MEASURES

Ascertainment of a first SARS-CoV-2 associated hospital admissions: due to SARS-CoV-2, with SARS-CoV-2 as a contributory factor, incidental to SARS-CoV-2 infection, and hospital acquired SARS-CoV-2.

RESULTS

3 226 535 children and adolescents had a recorded first SARS-CoV-2 infection during the observation period, and 29 230 (0.9%) infections involved a SARS-CoV-2 associated hospital admission. The median length of stay was 2 (interquartile range 1-4) days) and 1710 of 29 230 (5.9%) SARS-CoV-2 associated admissions involved paediatric critical care. 70 deaths occurred in which covid-19 or paediatric inflammatory multisystem syndrome was listed as a cause, of which 55 (78.6%) were in participants with a SARS-CoV-2 associated hospital admission. SARS-CoV-2 was the cause or a contributory factor in 21 000 of 29 230 (71.8%) participants who were admitted to hospital and only 380 (1.3%) participants acquired infection as an inpatient and 7855 (26.9%) participants were admitted with incidental SARS-CoV-2 infection. Boys, younger children (<5 years), and those from ethnic minority groups or areas of high deprivation were more likely to be admitted to hospital (all P<0.001). The covid-19 vaccination programme in England has identified certain conditions as representing a higher risk of admission to hospital with SARS-CoV-2: 11 085 (37.9%) of participants admitted to hospital had evidence of such a condition, and a further 4765 (16.3%) of participants admitted to hospital had a medical or developmental health condition not included in the vaccination programme's list.

CONCLUSIONS

Most SARS-CoV-2 associated hospital admissions in children and adolescents in England were due to SARS-CoV-2 or SARS-CoV-2 was a contributory factor. These results should inform future public health initiatives and research.

Artificial intelligence in public health: the potential of epidemic early warning systems

The use of artificial intelligence (AI) to generate automated early warnings in epidemic surveillance by harnessing vast open-source data with minimal human intervention has the potential to be both revolutionary and highly sustainable. AI can overcome the challenges faced by weak health systems by detecting epidemic signals much earlier than traditional surveillance. AI-based digital surveillance is an adjunct to-not a replacement of-traditional surveillance and can trigger early investigation, diagnostics and responses at the regional level. This narrative review focuses on the role of AI in epidemic surveillance and summarises several current epidemic intelligence systems including ProMED-mail, HealthMap, Epidemic Intelligence from Open Sources, BlueDot, Metabiota, the Global Biosurveillance Portal, Epitweetr and EPIWATCH. Not all of these systems are AI-based, and some are only accessible to paid users. Most systems have large volumes of unfiltered data; only a few can sort and filter data to provide users with curated intelligence. However, uptake of these systems by public health authorities, who have been slower to embrace AI than their clinical counterparts, is low. The widespread adoption of digital open-source surveillance and AI technology is needed for the prevention of serious epidemics.

Assessment of COVID-19 as the Underlying Cause of Death Among Children and Young People Aged 0 to 19 Years in the US

Importance

COVID-19 was the underlying cause of death for more than 940 000 individuals in the US, including at least 1289 children and young people (CYP) aged 0 to 19 years, with at least 821 CYP deaths occurring in the 1-year period from August 1, 2021, to July 31, 2022. Because deaths among US CYP are rare, the mortality burden of COVID-19 in CYP is best understood in the context of all other causes of CYP death.

Objective

To determine whether COVID-19 is a leading (top 10) cause of death in CYP in the US.

Design, Setting, and Participants

This national population-level cross-sectional epidemiological analysis for the years 2019 to 2022 used data from the US Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) database on underlying cause of death in the US to identify the ranking of COVID-19 relative to other causes of death among individuals aged 0 to 19 years. COVID-19 deaths were considered in 12-month periods between April 1, 2020, and August 31, 2022, compared with deaths from leading non-COVID-19 causes in 2019, 2020, and 2021.

Main Outcomes and Measures

Cause of death rankings by total number of deaths, crude rates per 100 000 population, and percentage of all causes of death, using the National Center for Health Statistics 113 Selected Causes of Death, for ages 0 to 19 and by age groupings (<1 year, 1-4 years, 5-9 years, 10-14 years, 15-19 years).

Results

There were 821 COVID-19 deaths among individuals aged 0 to 19 years during the study period, resulting in a crude death rate of 1.0 per 100 000 population overall; 4.3 per 100 000 for those younger than 1 year; 0.6 per 100 000 for those aged 1 to 4 years; 0.4 per 100 000 for those aged 5 to 9 years; 0.5 per 100 000 for those aged 10 to 14 years; and 1.8 per 100 000 for those aged 15 to 19 years. COVID-19 mortality in the time period of August 1, 2021, to July 31, 2022, was among the 10 leading causes of death in CYP aged 0 to 19 years in the US, ranking eighth among all causes of deaths, fifth in disease-related causes of deaths (excluding unintentional injuries, assault, and suicide), and first in deaths caused by infectious or respiratory diseases when compared with 2019. COVID-19 deaths constituted 2% of all causes of death in this age group.

Conclusions and Relevance

The findings of this study suggest that COVID-19 was a leading cause of death in CYP. It caused substantially more deaths in CYP annually than any vaccine-preventable disease historically in the recent period before vaccines became available. Various factors, including underreporting and not accounting for COVID-19's role as a contributing cause of death from other diseases, mean that these estimates may understate the true mortality burden of COVID-19. The findings of this study underscore the public health relevance of COVID-19 to CYP. In the likely future context of sustained SARS-CoV-2 circulation, appropriate pharmaceutical and nonpharmaceutical interventions (eg, vaccines, ventilation, air cleaning) will continue to play an important role in limiting transmission of the virus and mitigating severe disease in CYP.

COVID-19 and children

There has been substantial research on adult COVID-19 and how to treat it. But how do severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections afflict children? The COVID-19 pandemic has yielded many surprises, not least that children generally develop less severe disease than older adults, which is unusual for a respiratory disease. However, some children can develop serious complications from COVID-19, such as multisystem inflammatory syndrome in children (MIS-C) and Long Covid, even after mild or asymptomatic COVID-19. Why this occurs in some and not others is an important question. Moreover, when children do contract COVID-19, understanding their role in transmission, especially in schools and at home, is crucial to ensuring effective mitigation measures. Therefore, in addition to nonpharmaceutical interventions, such as improved ventilation, there is a strong case to vaccinate children so as to reduce possible long-term effects from infection and to decrease transmission. But questions remain about whether vaccination might skew immune responses to variants in the long term. As the experts discuss below, more is being learned about these important issues, but much more research is needed to understand the long-term effects of COVID-19 in children.

Characteristics and impact of Long Covid: Findings from an online survey

BACKGROUND

Long Covid is a public health concern that needs defining, quantifying, and describing. We aimed to explore the initial and ongoing symptoms of Long Covid following SARS-CoV-2 infection and describe its impact on daily life.

METHODS

We collected self-reported data through an online survey using convenience non-probability sampling. The survey enrolled adults who reported lab-confirmed (PCR or antibody) or suspected COVID-19 who were not hospitalised in the first two weeks of illness. This analysis was restricted to those with self-reported Long Covid. Univariate comparisons between those with and without confirmed COVID-19 infection were carried out and agglomerative hierarchical clustering was used to identify specific symptom clusters, and their demographic and functional correlates.

RESULTS

We analysed data from 2550 participants with a median duration of illness of 7.6 months (interquartile range (IQR) 7.1-7.9). 26.5% reported lab-confirmation of infection. The mean age was 46.5 years (standard deviation 11 years) with 82.8% females and 79.9% of participants based in the UK. 89.5% described their health as good, very good or excellent before COVID-19. The most common initial symptoms that persisted were exhaustion, chest pressure/tightness, shortness of breath and headache. Cognitive dysfunction and palpitations became more prevalent later in the illness. Most participants described fluctuating (57.7%) or relapsing symptoms (17.6%). Physical activity, stress, and sleep disturbance commonly triggered symptoms. A third (32%) reported they were unable to live alone without any assistance at six weeks from start of illness. 16.9% reported being unable to work solely due to COVID-19 illness. 37.0% reported loss of income due to illness, and 64.4% said they were unable to perform usual activities/duties. Acute systems clustered broadly into two groups: a majority cluster (n = 2235, 88%) with cardiopulmonary predominant symptoms, and a minority cluster (n = 305, 12%) with multisystem symptoms. Similarly, ongoing symptoms broadly clustered in two groups; a majority cluster (n = 2243, 88.8%) exhibiting mainly cardiopulmonary, cognitive symptoms and exhaustion, and a minority cluster (n = 283, 11.2%) exhibiting more multisystem symptoms. Belonging to the more severe multisystem cluster was associated with more severe functional impact, lower income, younger age, being female, worse baseline health, and inadequate rest in the first two weeks of the illness, with no major differences in the cluster patterns when restricting analysis to the lab-confirmed subgroup.

CONCLUSION

This is an exploratory survey of Long Covid characteristics. Whilst this is a non-representative population sample, it highlights the heterogeneity of persistent symptoms, and the significant functional impact of prolonged illness following confirmed or suspected SARS-CoV-2 infection. To study prevalence, predictors and prognosis, research is needed in a representative population sample using standardised case definitions.

Health equality, race and pharmacogenomics

Pharmacogenomics is increasingly moving into mainstream clinical practice. Careful consideration must be paid to inclusion of diverse populations in research, translation and implementation, in the historical and social context of population stratification, to ensure that this leads to improvements in healthcare for all rather than increased health disparities. This review takes a broad and critical approach to the current role of diversity in pharmacogenomics and addresses potential pitfalls in order to raise awareness for prescribers. It also emphasizes evidence gaps and suggests approaches that may minimize negative consequences and promote health equality.

Vaccinating adolescents against SARS-CoV-2 in England: a risk-benefit analysis

OBJECTIVE

To offer a quantitative risk-benefit analysis of two doses of SARS-CoV-2 vaccination among adolescents in England.

SETTING

England.

DESIGN

Following the risk-benefit analysis methodology carried out by the US Centers for Disease Control, we calculated historical rates of hospital admission, Intensive Care Unit admission and death for ascertained SARS-CoV-2 cases in children aged 12-17 in England. We then used these rates alongside a range of estimates for incidence of long COVID, vaccine efficacy and vaccine-induced myocarditis, to estimate hospital and Intensive Care Unit admissions, deaths and cases of long COVID over a period of 16 weeks under assumptions of high and low case incidence.

PARTICIPANTS

All 12-17 year olds with a record of confirmed SARS-CoV-2 infection in England between 1 July 2020 and 31 March 2021 using national linked electronic health records, accessed through the British Heart Foundation Data Science Centre.

MAIN OUTCOME MEASURES

Hospitalisations, Intensive Care Unit admissions, deaths and cases of long COVID averted by vaccinating all 12-17 year olds in England over a 16-week period under different estimates of future case incidence.

RESULTS

At high future case incidence of 1000/100,000 population/week over 16 weeks, vaccination could avert 4430 hospital admissions and 36 deaths over 16 weeks. At the low incidence of 50/100,000/week, vaccination could avert 70 hospital admissions and two deaths over 16 weeks. The benefit of vaccination in terms of hospitalisations in adolescents outweighs risks unless case rates are sustainably very low (below 30/100,000 teenagers/week). Benefit of vaccination exists at any case rate for the outcomes of death and long COVID, since neither have been associated with vaccination to date.

CONCLUSIONS

Given the current (as at 15 September 2021) high case rates (680/100,000 population/week in 10-19 year olds) in England, our findings support vaccination of adolescents against SARS-CoV2.

Uncertainty around the Long-Term Implications of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 231 million people globally, with more than 4.7 million deaths recorded by the World Health Organization as of 26 September 2021. In response to the pandemic, some countries (New Zealand, Vietnam, Taiwan, South Korea and others) have pursued suppression strategies, so-called Zero COVID policies, to drive and maintain infection rates as close to zero as possible and respond aggressively to new cases. In comparison, European countries and North America have adopted mitigation strategies (of varying intensity and effectiveness) that aim primarily to prevent health systems from being overwhelmed. With recent advances in our understanding of SARS-CoV-2 and its biology, and the increasing recognition there is more to COVID-19 beyond the acute infection, we offer a perspective on some of the long-term risks of mutational escape, viral persistence, reinfection, immune dysregulation and neurological and multi-system complications (Long COVID).

Modelling the impact of lockdown-easing measures on cumulative COVID-19 cases and deaths in England

OBJECTIVES

To assess the potential impacts of successive lockdown-easing measures in England, at a point in the COVID-19 pandemic when community transmission levels were relatively high.

DESIGN

We developed a Bayesian model to infer incident cases and reproduction number (R) in England, from incident death data. We then used this to forecast excess cases and deaths in multiple plausible scenarios in which R increases at one or more time points.

SETTING

England.

PARTICIPANTS

Publicly available national incident death data for COVID-19 were examined.

PRIMARY OUTCOME

Excess cumulative cases and deaths forecast at 90 days, in simulated scenarios of plausible increases in R after successive easing of lockdown in England, compared with a baseline scenario where R remained constant.

RESULTS

Our model inferred an R of 0.75 on 13 May when England first started easing lockdown. In the most conservative scenario modelled where R increased to 0.80 as lockdown was eased further on 1 June and then remained constant, the model predicted an excess 257 (95% CI 108 to 492) deaths and 26 447 (95% CI 11 105 to 50 549) cumulative cases over 90 days. In the scenario with maximal increases in R (but staying ≤1), the model predicts 3174 (95% CI 1334 to 6060) excess cumulative deaths and 421 310 (95% CI 177 012 to 804 811) cases. Observed data from the forecasting period aligned most closely to the scenario in which R increased to 0.85 on 1 June, and 0.9 on 4 July.

CONCLUSIONS

When levels of transmission are high, even small changes in R with easing of lockdown can have significant impacts on expected cases and deaths, even if R remains ≤1. This will have a major impact on population health, tracing systems and healthcare services in England. Following an elimination strategy rather than one of maintenance of R ≤1 would substantially mitigate the impact of the COVID-19 epidemic within England.

Distinct genetic architectures and environmental factors associate with host response to the γ2-herpesvirus infections

Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr Virus (EBV) establish life-long infections and are associated with malignancies. Striking geographic variation in incidence and the fact that virus alone is insufficient to cause disease, suggests other co-factors are involved. Here we present epidemiological analysis and genome-wide association study (GWAS) in 4365 individuals from an African population cohort, to assess the influence of host genetic and non-genetic factors on virus antibody responses. EBV/KSHV co-infection (OR = 5.71(1.58-7.12)), HIV positivity (OR = 2.22(1.32-3.73)) and living in a more rural area (OR = 1.38(1.01-1.89)) are strongly associated with immunogenicity. GWAS reveals associations with KSHV antibody response in the HLA-B/C region (p = 6.64 × 10^-09). For EBV, associations are identified for VCA (rs71542439, p = 1.15 × 10^-12). Human leucocyte antigen (HLA) and trans-ancestry fine-mapping substantiate that distinct variants in HLA-DQA1 (p = 5.24 × 10^-44) are driving associations for EBNA-1 in Africa. This study highlights complex interactions between KSHV and EBV, in addition to distinct genetic architectures resulting in important differences in pathogenesis and transmission.

Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa

Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.

An Ancient Baboon Genome Demonstrates Long-Term Population Continuity in Southern Africa

Baboons are one of the most abundant large nonhuman primates and are widely studied in biomedical, behavioral, and anthropological research. Despite this, our knowledge of their evolutionary and demographic history remains incomplete. Here, we report a 0.9-fold coverage genome sequence from a 5800-year-old baboon from the site of Ha Makotoko in Lesotho. The ancient baboon is closely related to present-day Papio ursinus individuals from southern Africa-indicating a high degree of continuity in the southern African baboon population. This level of population continuity is rare in recent human populations but may provide a good model for the evolution of Homo and other large primates over similar timespans in structured populations throughout Africa.

The ferroportin Q248H mutation protects from anemia, but not malaria or bacteremia

Iron acquisition is critical for life. Ferroportin (FPN) exports iron from mature erythrocytes, and deletion of the Fpn gene results in hemolytic anemia and increased fatality in malaria-infected mice. The FPN Q248H mutation (glutamine to histidine at position 248) renders FPN partially resistant to hepcidin-induced degradation and was associated with protection from malaria in human studies of limited size. Using data from cohorts including over 18,000 African children, we show that the Q248H mutation is associated with modest protection against anemia, hemolysis, and iron deficiency, but we found little evidence of protection against severe malaria or bacteremia. We additionally observed no excess Plasmodium growth in Q248H erythrocytes ex vivo, nor evidence of selection driven by malaria exposure, suggesting that the Q248H mutation does not protect from malaria and is unlikely to deprive malaria parasites of iron essential for their growth.

Author Correction: Genomics of disease risk in globally diverse populations

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Complimentary Methods for Multivariate Genome-Wide Association Study Identify New Susceptibility Genes for Blood Cell Traits

Genome-wide association studies (GWAS) have found hundreds of novel loci associated with full blood count (FBC) phenotypes. However, most of these studies were performed in a single phenotype framework without putting into consideration the clinical relatedness among traits. In this work, in addition to the standard univariate GWAS, we also use two different multivariate methods to perform the first multiple traits GWAS of FBC traits in ∼7000 individuals from the Ugandan General Population Cohort (GPC). We started by performing the standard univariate GWAS approach. We then performed our first multivariate method, in this approach, we tested for marker associations with 15 FBC traits simultaneously in a multivariate mixed model implemented in GEMMA while accounting for the relatedness of individuals and pedigree structures, as well as population substructure. In this analysis, we provide a framework for the combination of multiple phenotypes in multivariate GWAS analysis and show evidence of multi-collinearity whenever the correlation between traits exceeds the correlation coefficient threshold of r ² >=0.75. This approach identifies two known and one novel loci. In the second multivariate method, we applied principal component analysis (PCA) to the same 15 correlated FBC traits. We then tested for marker associations with each PC in univariate linear mixed models implemented in GEMMA. We show that the FBC composite phenotype as assessed by each PC expresses information that is not completely encapsulated by the individual FBC traits, as this approach identifies three known and five novel loci that were not identified using both the standard univariate and multivariate GWAS methods. Across both multivariate methods, we identified six novel loci. As a proof of concept, both multivariate methods also identified known loci, HBB and ITFG3. The two multivariate methods show that multivariate genotype-phenotype methods increase power and identify novel genotype-phenotype associations not found with the standard univariate GWAS in the same dataset.

Long reads: their purpose and place

In recent years long-read technologies have moved from being a niche and specialist field to a point of relative maturity likely to feature frequently in the genomic landscape. Analogous to next generation sequencing, the cost of sequencing using long-read technologies has materially dropped whilst the instrument throughput continues to increase. Together these changes present the prospect of sequencing large numbers of individuals with the aim of fully characterizing genomes at high resolution. In this article, we will endeavour to present an introduction to long-read technologies showing: what long reads are; how they are distinct from short reads; why long reads are useful and how they are being used. We will highlight the recent developments in this field, and the applications and potential of these technologies in medical research, and clinical diagnostics and therapeutics.

The First Norovirus Longitudinal Seroepidemiological Study From Sub-Saharan Africa Reveals High Seroprevalence of Diverse Genotypes Associated With Host Susceptibility Factors

Background

Human noroviruses (HuNoVs) are a prominent cause of gastroenteritis, yet fundamental questions remain regarding epidemiology, diversity, and immunity in sub-Saharan African children. We investigated HuNoV seroprevalence and genetic and sociodemographic risk factors in Ugandan children.

Methods

We randomly screened 797 participants of a longitudinal birth cohort (Entebbe, EMaBS) and 378 from a cross-sectional survey (rural Lake Victoria, LaVIISWA), for antibodies against HuNoV genotypes by ELISA. We used linear regression modeling to test for associations between HuNoV antibody levels and sociodemographic factors, and with the human susceptibility rs601338 FUT2 secretor SNP and histo-blood group antigens (A/B/O).

Results

Of EMaBS participants, 76.6% were seropositive by age 1, rising to 94.5% by age 2 years. Seroprevalence in 1 year olds of the rural LaVIISWA survey was even higher (95%). In the birth cohort, 99% of seropositive 2 year olds had responses to multiple HuNoV genotypes. We identified associations between secretor status and genogroup GII antibody levels (GII.4 P = 3.1 × 10-52), as well as ABO and GI (GI.2 P = 2.1 × 10-12).

Conclusions

HuNoVs are highly prevalent in Ugandan children, indicating a substantial burden of diarrhea-associated morbidity with recurrent infections. Public health interventions, including vaccination, and increased surveillance are urgently needed.

HIV treatment is associated with a two-fold higher probability of raised triglycerides: Pooled Analyses in 21 023 individuals in sub-Saharan Africa

BACKGROUND

Anti-retroviral therapy (ART) regimes for HIV are associated with raised levels of circulating triglycerides (TG) in western populations. However, there are limited data on the impact of ART on cardiometabolic risk in sub-Saharan African (SSA) populations.

METHODS

Pooled analyses of 14 studies comprising 21 023 individuals, on whom relevant cardiometabolic risk factors (including TG), HIV and ART status were assessed between 2003 and 2014, in SSA. The association between ART and raised TG (>2.3 mmol/L) was analysed using regression models.

FINDINGS

Among 10 615 individuals, ART was associated with a two-fold higher probability of raised TG (RR 2.05, 95% CI 1.51-2.77, I2=45.2%). The associations between ART and raised blood pressure, glucose, HbA1c, and other lipids were inconsistent across studies.

INTERPRETATION

Evidence from this study confirms the association of ART with raised TG in SSA populations. Given the possible causal effect of raised TG on cardiovascular disease (CVD), the evidence highlights the need for prospective studies to clarify the impact of long term ART on CVD outcomes in SSA.

Evaluating the Impact of Functional Genetic Variation on HIV-1 Control

Background

Previous genetic association studies of human immunodeficiency virus-1 (HIV-1) progression have focused on common human genetic variation ascertained through genome-wide genotyping.

Methods

We sought to systematically assess the full spectrum of functional variation in protein coding gene regions on HIV-1 progression through exome sequencing of 1327 individuals. Genetic variants were tested individually and in aggregate across genes and gene sets for an influence on HIV-1 viral load.

Results

Multiple single variants within the major histocompatibility complex (MHC) region were observed to be strongly associated with HIV-1 outcome, consistent with the known impact of classical HLA alleles. However, no single variant or gene located outside of the MHC region was significantly associated with HIV progression. Set-based association testing focusing on genes identified as being essential for HIV replication in genome-wide small interfering RNA (siRNA) and clustered regularly interspaced short palindromic repeats (CRISPR) studies did not reveal any novel associations.

Conclusions

These results suggest that exonic variants with large effect sizes are unlikely to have a major contribution to host control of HIV infection.

Tracing the route of modern humans out of Africa by using 225 human genome sequences from Ethiopians and Egyptians

The predominantly African origin of all modern human populations is well established, but the route taken out of Africa is still unclear. Two alternative routes, via Egypt and Sinai or across the Bab el Mandeb strait into Arabia, have traditionally been proposed as feasible gateways in light of geographic, paleoclimatic, archaeological, and genetic evidence. Distinguishing among these alternatives has been difficult. We generated 225 whole-genome sequences (225 at 8× depth, of which 8 were increased to 30×; Illumina HiSeq 2000) from six modern Northeast African populations (100 Egyptians and five Ethiopian populations each represented by 25 individuals). West Eurasian components were masked out, and the remaining African haplotypes were compared with a panel of sub-Saharan African and non-African genomes. We showed that masked Northeast African haplotypes overall were more similar to non-African haplotypes and more frequently present outside Africa than were any sets of haplotypes derived from a West African population. Furthermore, the masked Egyptian haplotypes showed these properties more markedly than the masked Ethiopian haplotypes, pointing to Egypt as the more likely gateway in the exodus to the rest of the world. Using five Ethiopian and three Egyptian high-coverage masked genomes and the multiple sequentially Markovian coalescent (MSMC) approach, we estimated the genetic split times of Egyptians and Ethiopians from non-African populations at 55,000 and 65,000 years ago, respectively, whereas that of West Africans was estimated to be 75,000 years ago. Both the haplotype and MSMC analyses thus suggest a predominant northern route out of Africa via Egypt.

The African Genome Variation Project shapes medical genetics in Africa

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.

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

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.

A general approach for haplotype phasing across the full spectrum of relatedness

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.

An evaluation of HIV elite controller definitions within a large seroconverter cohort collaboration

Background

Understanding the mechanisms underlying viral control is highly relevant to vaccine studies and elite control (EC) of HIV infection. Although numerous definitions of EC exist, it is not clear which, if any, best identify this rare phenotype.

Methods

We assessed a number of EC definitions used in the literature using CASCADE data of 25,692 HIV seroconverters. We estimated proportions maintaining EC of total ART-naïve follow-up time, and disease progression, comparing to non-EC. We also examined HIV-RNA and CD4 values and CD4 slope during EC and beyond (while ART naïve).

Results

Most definitions classify ∼1% as ECs with median HIV-RNA 43–903 copies/ml and median CD4>500 cells/mm³. Beyond EC status, median HIV-RNA levels remained low, although often detectable, and CD4 values high but with strong evidence of decline for all definitions. Median % ART-naïve time as EC was ≥92% although overlap between definitions was low. EC definitions with consecutive HIV-RNA measurements <75 copies/ml with follow-up≥ six months, or with 90% of measurements <400 copies/ml over ≥10 year follow-up preformed best overall. Individuals thus defined were less likely to progress to endpoint (hazard ratios ranged from 12.5–19.0 for non-ECs compared to ECs).

Conclusions

ECs are rare, less likely to progress to clinical disease, but may eventually lose control. We suggest definitions requiring individuals to have consecutive undetectable HIV-RNA measurements for ≥ six months or otherwise with >90% of measurements <400 copies/ml over ≥10 years be used to define this phenotype.

The association between circulating lipoprotein(a) and type 2 diabetes: is it causal?

Epidemiological evidence supports a direct and causal association between lipoprotein(a) [Lp(a)] levels and coronary risk, but the nature of the association between Lp(a) levels and risk of type 2 diabetes (T2D) is unclear. In this study, we assessed the association of Lp(a) levels with risk of incident T2D and tested whether Lp(a) levels are causally linked to T2D. We analyzed data on 18,490 participants from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort that included adults aged 40-79 years at baseline 1993-1997. During an average 10 years of follow-up, 593 participants developed incident T2D. Cox regression models were used to estimate the association between Lp(a) levels and T2D. In Mendelian randomization analyses, based on EPIC-Norfolk combined with DIAbetes Genetics Replication And Meta-analysis data involving a total of 10,088 diabetes case participants and 68,346 control participants, we used a genetic variant (rs10455872) as an instrument to test whether the association between Lp(a) levels and T2D is causal. In adjusted analyses, there was an inverse association between Lp(a) levels and T2D: hazard ratio was 0.63 (95% CI 0.49-0.81; P trend = 0.003) comparing the top versus bottom quintile of Lp(a). In EPIC-Norfolk, a 1-SD increase in logLp(a) was associated with a lower risk of T2D (odds ratio [OR] 0.88 [95% CI: 0.80-0.95]). However, in Mendelian randomization analyses, a 1-SD increase in logLp(a) due to rs10455872, which explained 26.8% of the variability in Lp(a) levels, was not associated with risk of T2D (OR 1.03 [0.96-1.10]; P = 0.41). These prospective findings demonstrate a strong inverse association of Lp(a) levels with risk of T2D. However, a genetic variant that elevated Lp(a) levels was not associated with risk of T2D, suggesting that elevated Lp(a) levels are not causally associated with a lower risk of T2D.

Discovery and refinement of loci associated with lipid levels

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

Common variants associated with plasma triglycerides and risk for coronary artery disease

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10⁻⁸ for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

Lipoprotein(a) and risk of coronary, cerebrovascular, and peripheral artery disease: the EPIC-Norfolk prospective population study

OBJECTIVE

Although the association between circulating levels of lipoprotein(a) [Lp(a)] and risk of coronary artery disease (CAD) and stroke is well established, its role in risk of peripheral arterial disease (PAD) remains unclear. Here, we examine the association between Lp(a) levels and PAD in a large prospective cohort. To contextualize these findings, we also examined the association between Lp(a) levels and risk of stroke and CAD and studied the role of low-density lipoprotein as an effect modifier of Lp(a)-associated cardiovascular risk.

METHODS AND RESULTS

Lp(a) levels were measured in apparently healthy participants in the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort. Cox regression was used to quantify the association between Lp(a) levels and risk of PAD, stroke, and CAD outcomes. During 212 981 person-years at risk, a total of 2365 CAD, 284 ischemic stroke, and 596 PAD events occurred in 18 720 participants. Lp(a) was associated with PAD and CAD outcomes but not with ischemic stroke (hazard ratio per 2.7-fold increase in Lp(a) of 1.37, 95% CI 1.25-1.50, 1.13, 95% CI 1.04-1.22 and 0.91, 95% CI 0.79-1.03, respectively). Low-density lipoprotein cholesterol levels did not modify these associations.

CONCLUSIONS

Lp(a) levels were associated with future PAD and CAD events. The association between Lp(a) and cardiovascular disease was not modified by low-density lipoprotein cholesterol levels.