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1.
Blood Adv ; 5(14): 2839-2851, 2021 07 27.
Article in English | MEDLINE | ID: mdl-34283174

ABSTRACT

Individuals with monogenic disorders can experience variable phenotypes that are influenced by genetic variation. To investigate this in sickle cell disease (SCD), we performed whole-genome sequencing (WGS) of 722 individuals with hemoglobin HbSS or HbSß0-thalassemia from Baylor College of Medicine and from the St. Jude Children's Research Hospital Sickle Cell Clinical Research and Intervention Program (SCCRIP) longitudinal cohort study. We developed pipelines to identify genetic variants that modulate sickle hemoglobin polymerization in red blood cells and combined these with pain-associated variants to build a polygenic score (PGS) for acute vaso-occlusive pain (VOP). Overall, we interrogated the α-thalassemia deletion -α3.7 and 133 candidate single-nucleotide polymorphisms (SNPs) across 66 genes for associations with VOP in 327 SCCRIP participants followed longitudinally over 6 years. Twenty-one SNPs in 9 loci were associated with VOP, including 3 (BCL11A, MYB, and the ß-like globin gene cluster) that regulate erythrocyte fetal hemoglobin (HbF) levels and 6 (COMT, TBC1D1, KCNJ6, FAAH, NR3C1, and IL1A) that were associated previously with various pain syndromes. An unweighted PGS integrating all 21 SNPs was associated with the VOP event rate (estimate, 0.35; standard error, 0.04; P = 5.9 × 10-14) and VOP event occurrence (estimate, 0.42; standard error, 0.06; P = 4.1 × 10-13). These associations were stronger than those of any single locus. Our findings provide insights into the genetic modulation of VOP in children with SCD. More generally, we demonstrate the utility of WGS for investigating genetic contributions to the variable expression of SCD-associated morbidities.


Subject(s)
Anemia, Sickle Cell , Fetal Hemoglobin , Anemia, Sickle Cell/complications , Anemia, Sickle Cell/genetics , Child , Fetal Hemoglobin/genetics , Humans , Longitudinal Studies , Pain , Polymorphism, Single Nucleotide
2.
Epidemics ; 11: 1-6, 2015 Jun.
Article in English | MEDLINE | ID: mdl-25979276

ABSTRACT

BACKGROUND: As a major zoonotic pathogen, characterization of the infectivity and pathogenicity of Coxiella burnetii is essential to understand Q-fever epidemiology. OBJECTIVES: We want to extend a recently published human dose response model based on experimental challenge of young adult males to include other age groups and both genders. Additionally, we can estimate the spatial distribution of exposure based on observed outbreak data. METHODS: Dose response assessment based on human challenge, is extended by including outbreak data, using location of cases as a proxy for exposure. This allows estimation of the influence of age and gender on the probability of developing symptoms of acute respiratory illness. RESULTS: In an outbreak in Switzerland, in 1983, exposure to C. burnetii was shown to depend strongly on distance from the source. The susceptibility of males to develop Q-fever decreases with age, while in females, middle-aged women appear to have the lowest risk. CONCLUSIONS: The published dose response model for Q-fever, based on experimental challenge of a small group of human volunteers, has been updated with data from a well studied outbreak. Infectivity estimates remain high, and even low doses (of 10 or fewer organisms) cause a high risk of illness.


Subject(s)
Coxiella burnetii/pathogenicity , Disease Outbreaks/statistics & numerical data , Q Fever/epidemiology , Adolescent , Adult , Age Factors , Child , Child, Preschool , Female , Humans , Incidence , Infant , Male , Middle Aged , Sex Factors , Switzerland/epidemiology , Young Adult
3.
BMC Public Health ; 14: 147, 2014 Feb 11.
Article in English | MEDLINE | ID: mdl-24517715

ABSTRACT

BACKGROUND: Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. However, most surveillance and notification systems are affected by a degree of underestimation (UE) and therefore uncertainty surrounds the 'true' incidence of disease affecting morbidity and mortality rates. Surveillance systems fail to capture cases at two distinct levels of the surveillance pyramid: from the community since not all cases seek healthcare (under-ascertainment), and at the healthcare-level, representing a failure to adequately report symptomatic cases that have sought medical advice (underreporting). There are several methods to estimate the extent of under-ascertainment and underreporting. METHODS: Within the context of the ECDC-funded Burden of Communicable Diseases in Europe (BCoDE)-project, an extensive literature review was conducted to identify studies that estimate ascertainment or reporting rates for salmonellosis and campylobacteriosis in European Union Member States (MS) plus European Free Trade Area (EFTA) countries Iceland, Norway and Switzerland and four other OECD countries (USA, Canada, Australia and Japan). Multiplication factors (MFs), a measure of the magnitude of underestimation, were taken directly from the literature or derived (where the proportion of underestimated, under-ascertained, or underreported cases was known) and compared for the two pathogens. RESULTS: MFs varied between and within diseases and countries, representing a need to carefully select the most appropriate MFs and methods for calculating them. The most appropriate MFs are often disease-, country-, age-, and sex-specific. CONCLUSIONS: When routine data are used to make decisions on resource allocation or to estimate epidemiological parameters in populations, it becomes important to understand when, where and to what extent these data represent the true picture of disease, and in some instances (such as priority setting) it is necessary to adjust for underestimation. MFs can be used to adjust notification and surveillance data to provide more realistic estimates of incidence.


Subject(s)
Campylobacter Infections/epidemiology , Disease Notification/statistics & numerical data , Public Health Surveillance/methods , Salmonella Infections/epidemiology , Australia , Canada , Disease Outbreaks , Epidemiological Monitoring , Female , Humans , Iceland , Incidence , Japan , Male , Norway , Public Health , Switzerland
4.
BMC Infect Dis ; 13: 488, 2013 Oct 21.
Article in English | MEDLINE | ID: mdl-24138807

ABSTRACT

BACKGROUND: The recent outbreak of Q fever in the Netherlands between 2007 and 2009 is the largest recorded Q fever outbreak. Exposure to Coxiella burnetii may cause Q fever but the size of the population exposed during the outbreak remained uncertain as little is known of the infectivity of this pathogen. The quantification of the infectiousness and the corresponding response is necessary for assessing the risk to the population. METHODS: A human challenge study was published in the 1950s but this study quantified the dose of C. burnetii in relative units. Data from a concurrent guinea pig challenge study were combined with a recent study in which guinea pigs were challenged with a similar aerosol route to quantify human exposure. Concentration estimates for C. burnetii are made jointly with estimates of the dose response parameters in a hierarchical Bayesian framework. RESULTS: The dose for 50% infection (InfD50%) in human subjects is 1.18 bacteria (95% credible interval (CI) 0.76-40.2). The dose for 50% illness (IllD50) in challenged humans is 5.58 (95%CI 0.89-89.0) bacteria. The probability of a single viable C. burnetii causing infection in humans is 0.44 (95%CI 0.044-0.59) and for illness 0.12 (95%CI 0.0006-0.55). CONCLUSIONS: To our knowledge this is the first human dose-response model for C. burnetii. The estimated dose response relation demonstrates high infectivity in humans. In many published papers the proportion of infected individuals developing illness is reported to be 40%. Our model shows that the proportion of symptomatic infections may vary with the exposure dose. This implies that presence of these bacteria in the environment, even in small numbers, poses a serious health risk to the population.


Subject(s)
Coxiella burnetii/isolation & purification , Q Fever/microbiology , Air Microbiology , Animals , Disease Outbreaks , Guinea Pigs , Humans , Middle Aged , Netherlands/epidemiology , Poisson Distribution , Q Fever/epidemiology , Q Fever/transmission , Risk Assessment
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