Biology subjects

Holmes, C.

Publications and source records attributed to Holmes, C..

5 recordsLinked to original sources

bioRxiv2018

Gene-Based Analysis in HRC Imputed Genome Wide Association Data Identifies Three Novel Genes For Alzheimer’s Disease

A novel POLARIS gene-based analysis approach was employed to compute gene-based polygenic risk score (PRS) for all individuals in the latest HRC imputed GERAD (N cases=3,332 and N controls=9,832) data using the International Genomics of Alzheimers Project summary statistics (N cases=13,676 and N controls=27,322, excluding GERAD subjects) to identify the SNPs and weight their risk alleles for the PRS score. SNPs were assigned to known, protein coding genes using GENCODE (v19). SNPs are assigned using both 1) no window around the gene and 2) a window of 35kb upstream and 10kb downstream to include transcriptional regulatory elements. The overall association of a gene is determined using a logistic regression model, adjusting for population covariates.\n\nThree novel gene-wide significant genes were determined from the POLARIS gene-based analysis using a gene window; PPARGC1A, RORA and ZNF423. The ZNF423 gene resides in an Alzheimers disease (AD)-specific protein network which also includes other AD-related genes. The PPARGC1A gene has been linked to energy metabolism and the generation of amyloid beta plaques and the RORA has strong links with genes which are differentially expressed in the hippocampus. We also demonstrate no enrichment for genes in either loss of function intolerant or conserved noncoding sequence regions.

genetics↗

bioRxiv2018

Interferon lambda 4 impacts broadly on hepatitis C virus diversity.

Type III interferons (IFN-{lambda}) are part of the innate immune response to hepatitis C virus (HCV) infection however the specific role of IFN-{lambda}4 and the nature of the viral adaption to this pressure have not been defined. Here we use paired genome-wide human and viral genetic data in 485 patients infected with HCV genotype 3a to explore the role of IFN-{lambda}4 on HCV evolution during chronic infection. We show that genetic variations within the host IFNL4 locus have a broad and systematic impact on HCV amino acid diversity. We also demonstrate that this impact is larger in patients producing a more active form of IFN-{lambda}4 protein compared to the less active form. A similar observation was noted for viral load. We conclude that IFN-{lambda}4 protein is a likely causal agent driving widespread HCV amino acid changes and associated with viral load and possibly other clinical and biological outcomes of HCV infection.

genomics↗

bioRxiv2018

GWAS identifies 10 loci for objectively-measured physical activity and sleep with causal roles in cardiometabolic disease.

Physical activity and sleep disorders are established risk factors for many diseases, but their etiology is poorly understood, partly due to a reliance on self-reported evidence. Here we report a genome-wide association study (GWAS) of wearable-defined and machine-learned physical activity and sleep phenotypes in 91,112 UK Biobank participants, and self-reported physical activity in 351,154 UK Biobank participants. While the self-reported activity analysis resulted in no significant (p<5x10-9) loci, the analysis of objectively-measured traits identified 10 loci, 6 of which are novel. These 10 loci account for 0.05% of activity and 0.33% of sleep phenotype variation, but genome-wide estimates suggest that common variation accounts for ~12% of phenotypic variation, indicating high polygenicity. Heritability was higher in women than in men for overall activity ({Delta}h2 = 4%, p=6.3x10-5), moderate intensity activity (6%, p=6.7x10-8), and walking (5%, p=2.6x10-6). Heritability partitioning, enrichment and pathway analyses all indicate the central nervous system plays a role in activity behaviours. Mendelian randomization in publicly available GWAS data and in 278,367 UK Biobank participants, who were not included in our discovery analyses, suggest that overall activity might be causally related to lowering body fat percentage (beta per SD higher overall activity: -0.44, SE=0.047, p=2.70x10-21) and systolic blood pressure (beta per SD: -0.71, SE=0.125, p=1.38x10-8). Our current results advocate the value of physical activity for the reduction of adiposity and blood pressure.

genetics↗

bioRxiv2017

Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,609 UK Biobank participants

Current public health guidelines on physical activity and sleep duration are limited by a reliance on subjective self-reported evidence. Using data from simple wrist-worn activity monitors, we developed a tailored machine learning model, using balanced random forests with Hidden Markov Models, to reliably detect a number of activity modes. We show that physical activity and sleep behaviours can be classified with 87% accuracy in 159,504 minutes of recorded free-living behaviours from 132 adults. These trained models can be used to infer fine resolution activity patterns at the population scale in 96,220 participants. For example, we find that men spend more time in both low- and high-intensity behaviours, while women spend more time in mixed behaviours. Walking time is highest in spring and sleep time lowest during the summer. This work opens the possibility of future public health guidelines informed by the health consequences associated with specific, objectively measured, physical activity and sleep behaviours.

bioinformatics↗

bioRxiv2017

Dehydration Bouts Prompt Increased Activity And Blood Feeding By Mosquitoes

Mosquitoes are prone to dehydration and respond to this stress through multiple mechanisms, but previous studies have examined very specific responses and fail to provide an encompassing view of the role that dehydration has on mosquito biology. This study examined underlying changes in biology of the northern house mosquito, Culex pipiens, associated with short bouts of dehydration. We show that dehydration increased blood feeding propensity of mosquitoes, which was the result of both enhanced activity and a higher tendency to land on a host. Mosquitoes exposed to dehydrating conditions with access to water or rehydrated individuals experience no water loss and failed to display behavioral changes. RNA-seq and metabolome analyses following dehydration indicated that factors associated with energy metabolism are altered, specifically the breakdown of trehalose to yield glucose, which likely underlies changes in mosquito activity. Suppression of trehalose breakdown by RNA interference reduced phenotypes associated with dehydration. Comparable results were noted for two other mosquito species, suggesting this is a general response among mosquitoes. Lastly, field-based mesocosm studies using C. pipiens revealed that dehydrated mosquitoes were more likely to host feed, and disease modeling indicates dehydration bouts may increase transmission of West Nile virus. These results suggest that periods of dehydration prompt mosquitoes to utilize blood feeding as a mechanism to obtain water. This dehydration-induced increase in blood feeding is likely to intensify disease transmission during periods of low water availability.\n\nSignificanceDehydration stress has substantial impacts on the biology of terrestrial invertebrates. To date, no studies have elucidated the difference between dehydration exposure and realized water loss in relation to mosquito behavior and physiology. Our experiments show that direct dehydration stress increases mosquito activity and subsequent blood feeding, likely as a mechanism to locate and utilize a bloodmeal for rehydration. These dehydration-induced phenotypes were linked to altered carbohydrate metabolism that acts as a source of energy. This study provides important insight into the impact of mosquito-dehydration dynamics on disease transmission that is likely general among mosquitoes.

physiology↗