New treatments in Alzheimer’s disease

Alzheimer’s disease is the most common cause of dementia, affecting around 50 million people worldwide. Its prevalence is increasing mainly as a result of an ageing population with considerable associated increases in health and social care costs. As a result, government agencies worldwide have turned funding streams towards unravelling biological mechanisms and developing therapeutic opportunities for the dementias in general. Consequently, a number of novel potential treatments have been developed, although, to date, they have not been shown to significantly alter disease course. In this month’s journal club we look at three large clinical trials of new treatments in Alzheimer’s disease

Cannabidiol as a treatment for epilepsy

Despite an increasing number of anti-epileptic drugs (AEDs), the proportion of drug-resistant cases of epilepsy has remained fairly static at around 30% and the search for new and improved AEDs continues. Cannabis has been used as a medical treatment for epilepsy for thousands of years; it contains many active compounds, the most important being tetrahydrocannabinol, which has psychoactive properties, and cannabidiol, which does not. Animal models and clinical data to date have suggested that cannabidiol is more useful in treating epilepsy; there is limited evidence that tetrahydrocannabinol has some pro-convulsant effects in animal models. The mechanism by which cannabidiol exerts its anti-convulsant properties is currently unclear. This month’s journal club reviews three papers using cannabidiol for the treatment of epilepsy. The first paper describes a small case series where cannabidiol is used in a rare pediatric epilepsy syndrome, febrile infection-related epilepsy syndrome (FIRES); the second paper is a larger open label study of cannabidiol in a variety of refractory epilepsies and the third paper describes a randomized control trial of cannabidiol in Dravet syndrome

Weight change associated with antiepileptic drugs

Aim To investigate antiepileptic drug (AED)-related weight changes in patients with epilepsy through a retrospective observational study. Method We analysed the anonymised electronic primary care records of 1.1 million adult patients in Wales. We included patients aged 18 years and over with a diagnosis of epilepsy, whose body weight had been measured up to 12 months before starting, and between 3 and 12 months after starting, one of five AEDs. We calculated the weight difference after starting the AED for each patient. Results 1423 patients were identified in total. The mean difference between body weight after and before starting each AED (together with 95% CI and p values for no difference) were: carbamazepine (CBZ) 0.43 (−0.19 to 1.05) p=0.17; lamotrigine (LTG) 0.31 (−0.38 to 1.00) p=0.38; levetiracetam (LEV) 1.00 (0.16 to 1.84) p=0.02; sodium valproate (VPA) 0.74 (0.10 to 1.38) p=0.02; topiramate (TPM) −2.30 (−4.27 to −0.33) p=0.02. Conclusions LEV and VPA were associated with significant weight gain, TPM was associated with significant weight loss, and LTG and CBZ were not associated with significant weight change

Increased levels of noisy splicing in cancers, but not for oncogene-derived transcripts

Recent genome-wide analyses have detected numerous cancer-specific alternative splicing (AS) events. Whether transcripts containing cancer-specific AS events are likely to be translated into functional proteins or simply reflect noisy splicing, thereby determining their clinical relevance, is not known. Here we show that consistent with a noisy-splicing model, cancer-specific AS events generally tend to be rare, containing more premature stop codons and have less identifiable functional domains in both the human and mouse. Interestingly, common cancer-derived AS transcripts from tumour suppressor and oncogenes show marked changes in premature stop-codon frequency; with tumour suppressor genes exhibiting increased levels of premature stop codons whereas oncogenes have the opposite pattern. We conclude that tumours tend to have faithful oncogene splicing and a higher incidence of premature stop codons among tumour suppressor and cancer-specific splice variants showing the importance of considering splicing noise when analysing cancer-specific splicing changes

Exon-Specific QTLs Skew the Inferred Distribution of Expression QTLs Detected Using Gene Expression Array Data

Mapping of expression quantitative trait loci (eQTLs) is an important technique for studying how genetic variation affects gene regulation in natural populations. In a previous study using Illumina expression data from human lymphoblastoid cell lines, we reported that cis-eQTLs are especially enriched around transcription start sites (TSSs) and immediately upstream of transcription end sites (TESs). In this paper, we revisit the distribution of eQTLs using additional data from Affymetrix exon arrays and from RNA sequencing. We confirm that most eQTLs lie close to the target genes; that transcribed regions are generally enriched for eQTLs; that eQTLs are more abundant in exons than introns; and that the peak density of eQTLs occurs at the TSS. However, we find that the intriguing TES peak is greatly reduced or absent in the Affymetrix and RNA-seq data. Instead our data suggest that the TES peak observed in the Illumina data is mainly due to exon-specific QTLs that affect 3′ untranslated regions, where most of the Illumina probes are positioned. Nonetheless, we do observe an overall enrichment of eQTLs in exons versus introns in all three data sets, consistent with an important role for exonic sequences in gene regulation

Joint modelling of confounding factors and prominent genetic regulators provides increased accuracy in genetical genomics studies.

Expression quantitative trait loci (eQTL) studies are an integral tool to investigate the genetic component of gene expression variation. A major challenge in the analysis of such studies are hidden confounding factors, such as unobserved covariates or unknown subtle environmental perturbations. These factors can induce a pronounced artifactual correlation structure in the expression profiles, which may create spurious false associations or mask real genetic association signals. Here, we report PANAMA (Probabilistic ANAlysis of genoMic dAta), a novel probabilistic model to account for confounding factors within an eQTL analysis. In contrast to previous methods, PANAMA learns hidden factors jointly with the effect of prominent genetic regulators. As a result, this new model can more accurately distinguish true genetic association signals from confounding variation. We applied our model and compared it to existing methods on different datasets and biological systems. PANAMA consistently performs better than alternative methods, and finds in particular substantially more trans regulators. Importantly, our approach not only identifies a greater number of associations, but also yields hits that are biologically more plausible and can be better reproduced between independent studies. A software implementation of PANAMA is freely available online at http://ml.sheffield.ac.uk/qtl/

Inference of population splits and mixtures from genome-wide allele frequency data

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In this model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication, and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.comComment: 28 pages, 6 figures in main text. Attached supplement is 22 pages, 15 figures. This is an updated version of the preprint available at http://precedings.nature.com/documents/6956/version/

Scans for signatures of selection in Russian cattle breed genomes reveal new candidate genes for environmental adaptation and acclimation

Domestication and selective breeding has resulted in over 1000 extant cattle breeds. Many of these breeds do not excel in important traits but are adapted to local environments. These adaptations are a valuable source of genetic material for efforts to improve commercial breeds. As a step toward this goal we identified candidate regions to be under selection in genomes of nine Russian native cattle breeds adapted to survive in harsh climates. After comparing our data to other breeds of European and Asian origins we found known and novel candidate genes that could potentially be related to domestication, economically important traits and environmental adaptations in cattle. The Russian cattle breed genomes contained regions under putative selection with genes that may be related to adaptations to harsh environments (e.g., AQP5, RAD50, and RETREG1). We found genomic signatures of selective sweeps near key genes related to economically important traits, such as the milk production (e.g., DGAT1, ABCG2), growth (e.g., XKR4), and reproduction (e.g., CSF2). Our data point to candidate genes which should be included in future studies attempting to identify genes to improve the extant breeds and facilitate generation of commercial breeds that fit better into the environments of Russia and other countries with similar climates