Biology subjects

Leung, G. M.

Publications and source records attributed to Leung, G. M..

4 recordsLinked to original sources

bioRxiv2020

Identification of 2019-nCoV related coronaviruses in Malayan pangolins in southern China

The ongoing outbreak of viral pneumonia in China and beyond is associated with a novel coronavirus, provisionally termed 2019-nCoV. This outbreak has been tentatively associated with a seafood market in Wuhan, China, where the sale of wild animals may be the source of zoonotic infection. Although bats are likely reservoir hosts for 2019-nCoV, the identity of any intermediate host facilitating transfer to humans is unknown. Here, we report the identification of 2019-nCoV related coronaviruses in pangolins (Manis javanica) seized in anti-smuggling operations in southern China. Metagenomic sequencing identified pangolin associated CoVs that belong to two sub-lineages of 2019-nCoV related coronaviruses, including one very closely related to 2019-nCoV in the receptor-binding domain. The discovery of multiple lineages of pangolin coronavirus and their similarity to 2019-nCoV suggests that pangolins should be considered as possible intermediate hosts for this novel human virus and should be removed from wet markets to prevent zoonotic transmission.

microbiology↗

bioRxiv2019

The effect of liver enzymes on body composition: a Mendelian randomization study

BackgroundHigher alanine transaminase (ALT) is positively associated with diabetes but inversely associated with body mass index (BMI) in Mendelian randomization (MR) studies, suggesting liver function may affect body composition. To clarify, we assessed the association of liver function with muscle and fat mass observationally with two-sample MR as a validation.\n\nMethodsIn the population-representative \"Children of 1997\" birth cohort, we used multivariable linear regression to assess the adjusted associations of ALT and alkaline phosphatase (ALP) (IU/L) at ~17.5 years with muscle mass (kg) and body fat percentage (%). Genetic variants predicting ALT, ALP and gamma glutamyltransferase (GGT) (100% change in concentration) were applied to fat-free and fat mass (kg) in the UK Biobank (n=~331,000) to obtain unconfounded estimates using MR.\n\nResultsObservationally, ALT was positively associated with muscle mass (0.11, 95% confidence interval (CI) 0.10 to 0.12) and fat percentage (0.15, 95% CI 0.13 to 0.17). ALP was inversely associated with muscle mass (-0.03, 95% CI -0.04 to -0.02) and fat percentage (-0.02, 95% CI -0.03 to -0.01). Using MR, ALT was inversely associated with fat-free mass (-0.41, 95% CI -0.64 to -0.19) and fat mass (-0.58, 95% CI -0.85 to -0.30). ALP was not clearly associated with body composition. GGT was positively associated with fat-free (0.30, 95% CI 0.01 to 0.06) and fat mass (0.41, 95% CI 0.10 to 0.71).\n\nConclusionALT reducing fat-free mass provides a possible pathway for the positive association of ALT with diabetes, and suggests a potential target of intervention.

genetics↗

bioRxiv2018

The effect of liver enzymes on adiposity: a Mendelian randomization study

Poorer liver function is positively associated with diabetes in Mendelian randomization (MR) studies. Observationally, adiposity is associated with poorer liver function. To clarify the etiology, we assessed the association of liver function with adiposity observationally and using two sample MR for validation.\n\nIn the \"Children of 1997\" birth cohort, we used multivariable linear regression to assess the associations of ALT and alkaline phosphatase (ALP) (IU/L) at [~]17.5 years with body mass index (BMI) (kg/m2). Using MR, genetic variants predicting ALT, ALP and gamma glutamyltransferase (GGT) (100% change in concentration), were applied to genome-wide association studies of BMI, waist circumference (WC) and waist-hip ratio (WHR) (standard deviations) to obtain unconfounded inverse-variance weighting estimates.\n\nObservationally, ALT was positively associated with BMI (0.10, 95% confidence interval (CI) 0.09 to 0.11). ALP was inversely associated with BMI (-0.018, 95% CI -0.024 to -0.012). Using MR, ALT was inversely associated with BMI (-0.14, 95% CI -0.20 to -0.07), but not WC or WHR. ALP and GGT were unrelated to adiposity.\n\nPoorer liver function might not cause adiposity; instead higher ALT might reduce BMI. Whether ALT contributes to diabetes by reducing muscle mass, given the no association of ALT with WC or WHR, requires investigation.\n\nAbbreviations

epidemiology↗

bioRxiv2018

Age-specific differences in the dynamics of protective immunity to influenza

Influenza A viruses evolve rapidly to escape host immunity, such that individuals can be infected multiple times with the same subtype. The form and duration of protective immunity after each influenza infection are poorly understood. Here, we quantify the dynamics of protective immunity against influenza A virus infections by fitting individual-level mechanistic models to longitudinal serology from children and adults in a household cohort study. We find that most protection in children is explained by antibody titers measured by the hemagglutination inhibition (HI) assay. In contrast, in adults, HI antibody titers explain a smaller fraction of protection. Protection against circulating strains wanes to approximately 50% of peak levels 3.5-7 years after infection in both age groups, and wanes faster against influenza A(H3N2) than A(H1N1)pdm09. Protection against H3N2 lasts longer in adults than in children. Our results suggest that the focus of influenza antibody responses changes over time from the highly mutable hemagglutinin head to other epitopes, consistent with the immunological theory of original antigenic sin, and that this change of focus might affect protection. Additionally, we estimate that imprinting, or primary infection with a subtype of one phylogenetic group, has little to no effect on the risk of non-medically attended influenza infections in adults. We also find no evidence of long-term cross-protection between subtypes. This work underscores the need for longitudinal data on multiple components of the immune response to better understand the development of immunity and differences in susceptibility within populations.

epidemiology↗