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Cis-acting regulatory sequences are required for the proper temporal and spatial control of gene expression. Variation in gene expression is highly heritable and a significant determinant of human disease susceptibility. The diversity of human genetic diseases attributed, in whole or in part, to mutations in non-coding regulatory sequences is on the rise. Improvements in genome-wide methods of associating genetic variation with human disease and predicting DNA with cis-regulatory potential are two of the major reasons for these recent advances. This review will highlight select examples from the literature that have successfully integrated genetic and genomic approaches to uncover the molecular basis by which cis-regulatory mutations alter gene expression and contribute to human disease. The fine mapping of disease-causing variants has led to the discovery of novel cis-acting regulatory elements that, in some instances, are located as far away as 1.5 Mb from the target gene. In other cases, the prior knowledge of the regulatory landscape surrounding the gene of interest aided in the selection of enhancers for mutation screening. The success of these studies should provide a framework for following up on the large number of genome-wide association studies that have identified common variants in non-coding regions of the genome that associate with increased risk of human diseases including, diabetes, autism, Crohn's, colorectal cancer, and asthma, to name a few.

The identification of complex disease susceptibility loci has been accelerated considerably by advances in high-throughput genotyping technologies, improved insight into correlation patterns of common variants and the availability of large-scale sample sets. Linkage scans and small-scale candidate gene studies have now given way to genome-wide association scans. In this review, we summarize insights gained from the past, highlight practical issues relating to the design and analysis of current state-of-the-art GWA studies and look into future trends in the field of human complex trait genetics.

The ultimate goal of most shotgun proteomic pipelines is the discovery of novel biomarkers to direct the development of quantitative diagnostics for the detection and treatment of disease. Differential comparisons of biological samples identify candidate peptides that can serve as proxys of candidate proteins. While these discovery approaches are robust and fairly comprehensive, they have relatively low throughput. When merged with targeted mass spectrometry, this pipeline can fuel hypothesis-driven studies and the development of novel diagnostics and therapeutics.

A variety of stable isotope labeling techniques have been developed and used in mass spectrometry (MS)-based proteomics, primarily for relative quantitation of changes in protein abundances between two compared samples, but also for qualitative characterization of differentially labeled proteomes. Differential (16)O/(18)O coding relies on the (18)O exchange that takes place at the C-terminal carboxyl group of proteolytic fragments, where two (16)O atoms are typically replaced by two (18)O atoms by enzyme-catalyzed oxygen-exchange in the presence of H(2)(18)O. The resulting mass shift between differentially labeled peptide ions permits identification, characterization and quantitation of proteins from which the peptides are proteolytically generated. This review focuses on the utility of (16)O/(18)O labeling within the context of mass spectrometry-based proteome research. Different strategies employing (16)O/(18)O are examined in the context of global comparative proteome profiling, targeted subcellular proteomics, analysis of post-translational modifications and biomarker discovery. Also discussed are analytical issues related to this technique, including variable (18)O exchange along with advantages and disadvantages of (16)O/(18)O labeling in comparison with other isotope-coding techniques.

OBJECTIVES: Hearing, vision, and cognitive impairment commonly co-occur in older adults. Improving sensory function may positively impact outcomes in people with dementia (PwD). We developed a "sensory intervention" (SI) to support hearing and vision in PwD. Here, we report the findings of an international open-label field trial, and nested case series, to explore the impact of the SI on dementia-related outcomes.METHODS: This was a home-based trial conducted in France, England, and Cyprus. Participants were people with mild-to-moderate dementia and hearing and/or vision impairment (n = 19) and their study partners (unpaid carers; n = 19). The "basic" SI included a hearing and vision assessment and provision of glasses and/or hearing aids. A subsample received the "extended" SI with additional weekly visits from a sensory support therapist (SST). Exploratory analyses of dementia-related, health utility and resource utilisation outcomes were performed.RESULTS: Quality of life (QoL) and sensory functional ability improved. Change in QoL exceeded the threshold for a minimum clinically important difference. There was a modest improvement (in absolute terms) post intervention in behavioural disturbance, self-efficacy, and relationship satisfaction. Study partner time assisting instrumental activities of daily living (iADL) and supervision decreased by about 22 and 38 hours per month, respectively, although time for personal ADL support increased. Qualitative data supported effectiveness of the intervention: PwD were more socially engaged, less isolated, less dependent on study partners, and had improved functional ability and communication.CONCLUSIONS: These findings support the need for a definitive randomised controlled trial (RCT) to evaluate the effectiveness of the intervention.

Chromatin-immunoprecipitation and sequencing (ChIP-seq) is a rapidly maturing technology that draws on the power of high-throughput short-read sequencing to decipher chromatin states with unprecedented precision and breadth. Although some aspects of the experimental protocol require careful tuning, the bottleneck currently firmly lies with the downstream data analysis. We give an overview of the better-established aspects of genome mapping and data normalization and we describe the more recent progress in peak calling and their statistical analysis and provide a brief overview of popular follow-up analyses such as genomic feature categorization and motif search.