Genetics of common complex diseases: a view from Iceland

Motivating and Discouraging Factors for Bipolar Patient Participation in Genomic Research

AIMS

The goal of this project was to better understand the motivating and discouraging factors toward genetic research and biobank programs in patients with bipolar disorder, particularly across gender and racial identities.

METHODS

A survey (n = 63) of adults diagnosed with bipolar disorder was conducted at the general psychiatric inpatient unit and outpatient clinic at the University of Mississippi Medical Center. Participants were asked to rate on a Likert scale their attitudes toward medical research generally, mental health research specifically, and willingness to participate in a bipolar DNA biobank. Last, they were asked to endorse motivating factors or concerns for their attitude toward participation.

RESULTS

Neither attitudes toward research nor willingness to participate in a bipolar biobank differed across gender, age, or education level, but Black/African American participants were statistically significantly less likely to endorse a willingness to participate in a biobank compared to White participants. As observed in previous work, Black/African American participants were significantly more likely to endorse concerns regarding violations of trust, privacy, or autonomy. However, while there were no significant differences in discouraging factors among individuals who indicated an opposition to participating in a biobank compared to those who indicated support, there was a significant decrease in support of motivating factors, including increasing knowledge, personal benefit, and duty to community, for those not interested in participating.

CONCLUSIONS

Black/African American participants with bipolar disorder were more likely to express concerns about DNA and biobank research. But while race was a contributing factor to support or opposition to biobanking for bipolar disorder research, more salient was insufficient positive motivation. These results highlight the need to emphasize contemporary safeguards on DNA research and biobanking as an ethical duty and to identify the need for community-based educational interventions to promote a greater understanding of the positive benefits to motivate increased research participation.

Evolution of biosequence search algorithms: a brief survey

Motivation

Although modern high-throughput biomolecular technologies produce various types of data, biosequence data remain at the core of bioinformatic analyses. However, computational techniques for dealing with this data evolved dramatically.

Results

In this bird’s-eye review, we overview the evolution of main algorithmic techniques for comparing and searching biological sequences. We highlight key algorithmic ideas emerged in response to several interconnected factors: shifts of biological analytical paradigm, advent of new sequencing technologies and a substantial increase in size of the available data. We discuss the expansion of alignment-free techniques coming to replace alignment-based algorithms in large-scale analyses. We further emphasize recently emerged and growing applications of sketching methods which support comparison of massive datasets, such as metagenomics samples. Finally, we focus on the transition to population genomics and outline associated algorithmic challenges.

Analysis and Annotation of Whole-Genome or Whole-Exome Sequencing Derived Variants for Clinical Diagnosis

Over the last 10 years, next-generation sequencing (NGS) has transformed genomic research through substantial advances in technology and reduction in the cost of sequencing, and also in the systems required for analysis of these large volumes of data. This technology is now being used as a standard molecular diagnostic test in some clinical settings. The advances in sequencing have come so rapidly that the major bottleneck in identification of causal variants is no longer the sequencing or analysis (given access to appropriate tools), but rather clinical interpretation. Interpretation of genetic findings in a complex and ever changing clinical setting is scarcely a new challenge, but the task is increasingly complex in clinical genome-wide sequencing given the dramatic increase in dataset size and complexity. This increase requires application of appropriate interpretation tools, as well as development and application of appropriate methodologies and standard procedures. This unit provides an overview of these items. Specific challenges related to implementation of genome-wide sequencing in a clinical setting are discussed. © 2017 by John Wiley & Sons, Inc.