Integrative approach to pain genetics identifies pain sensitivity loci across diseases

Sources of Individual Differences in Pain

Pain is an immense clinical and societal challenge, and the key to understanding and treating it is variability. Robust interindividual differences are consistently observed in pain sensitivity, susceptibility to developing painful disorders, and response to analgesic manipulations. This review examines the causes of this variability, including both organismic and environmental sources. Chronic pain development is a textbook example of a gene-environment interaction, requiring both chance initiating events (e.g., trauma, infection) and more immutable risk factors. The focus is on genetic factors, since twin studies have determined that a plurality of the variance likely derives from inherited genetic variants, but sex, age, ethnicity, personality variables, and environmental factors are also considered.

Genome-wide SNP analysis of Siamese cobra (Naja kaouthia) reveals the molecular basis of transitions between Z and W sex chromosomes and supports the presence of an ancestral super-sex chromosome in amniotes

Elucidation of the process of sex chromosome differentiation is necessary to understand the dynamics of evolutionary mechanisms in organisms. The W sex chromosome of the Siamese cobra (Naja kaouthia) contains a large number of repeats and shares amniote sex chromosomal linkages. Diversity Arrays Technology provides an effective approach to identify sex-specific loci that are epoch-making, to understand the dynamics of molecular transitions between the Z and W sex chromosomes in a snake lineage. From a total of 543 sex-specific loci, 90 showed partial homology with sex chromosomes of several amniotes and 89 loci were homologous to transposable elements. Two loci were confirmed as W-specific nucleotides after PCR amplification. These loci might result from a sex chromosome differentiation process and involve putative sex-determination regions in the Siamese cobra. Sex-specific loci shared linkage homologies among amniote sex chromosomes, supporting an ancestral super-sex chromosome.

Integrative Analysis of Omics Big Data

The diversity and huge omics data take biology and biomedicine research and application into a big data era, just like that popular in human society a decade ago. They are opening a new challenge from horizontal data ensemble (e.g., the similar types of data collected from different labs or companies) to vertical data ensemble (e.g., the different types of data collected for a group of person with match information), which requires the integrative analysis in biology and biomedicine and also asks for emergent development of data integration to address the great changes from previous population-guided to newly individual-guided investigations.Data integration is an effective concept to solve the complex problem or understand the complicate system. Several benchmark studies have revealed the heterogeneity and trade-off that existed in the analysis of omics data. Integrative analysis can combine and investigate many datasets in a cost-effective reproducible way. Current integration approaches on biological data have two modes: one is "bottom-up integration" mode with follow-up manual integration, and the other one is "top-down integration" mode with follow-up in silico integration.This paper will firstly summarize the combinatory analysis approaches to give candidate protocol on biological experiment design for effectively integrative study on genomics and then survey the data fusion approaches to give helpful instruction on computational model development for biological significance detection, which have also provided newly data resources and analysis tools to support the precision medicine dependent on the big biomedical data. Finally, the problems and future directions are highlighted for integrative analysis of omics big data.

Significant Linkage Evidence for Interstitial Cystitis/Painful Bladder Syndrome on Chromosome 3

PURPOSE

Interstitial cystitis/painful bladder syndrome is a chronic pelvic pain condition of unknown etiology. We hypothesized that related interstitial cystitis/painful bladder syndrome cases were more likely to have a genetic etiology. The purpose of this study was to perform a genetic linkage analysis.

MATERIALS AND METHODS

We identified interstitial cystitis/painful bladder syndrome cases using diagnostic codes linked to the Utah Population Database genealogy resource and to electronic medical records. For this analysis we used 13 high risk pedigrees, defined as having a statistical excess number of interstitial cystitis/painful bladder syndrome cases among descendants compared to matched hospital population rates. Case status was confirmed in medical records using natural language processing. DNA was obtained from stored, nonneoplastic, formalin fixed, paraffin embedded tissue blocks. Each pedigree had at least 2 cases with DNA available. Parametric linkage analysis was performed.

RESULTS

Pedigrees ranged in size from 2 to 12 genotyped cases for a total of 48 cases. Significant genome wide linkage evidence was found under a dominant model on chromosome 3p13-p12.3 (maximum heterogeneity θ logarithm of odds 3.56). Two pedigrees showed at least nominal linkage evidence in this region (logarithm of odds greater than 0.59). The most informative pedigree included 12 interstitial cystitis/painful bladder syndrome cases (pedigree θ logarithm of odds 2.1). Other regions with suggestive linkage evidence included 1p21-q25, 3p21.1-p14.3, 4q12-q13, 9p24-p22 and 14q24-q31, all under a dominant model.

CONCLUSIONS

While the etiology of interstitial cystitis/painful bladder syndrome is unknown, this study provides evidence that a genetic variant(s) on chromosome 3 and possibly on chromosomes 1, 4, 9 and 14 contribute to an interstitial cystitis/painful bladder syndrome predisposition. Sequence analysis of affected cases in identified pedigrees may provide insight into genes contributing to interstitial cystitis/painful bladder syndrome.

Relationship of Genetic Variants With Procedural Pain, Anxiety, and Distress in Children

OBJECTIVE

This study used a candidate gene approach to examine genomic variation associated with pain, anxiety, and distress in children undergoing a medical procedure.

STUDY DESIGN

Children aged 4-10 years having an IV catheter insertion were recruited from three Midwestern children's hospitals. Self-report measures of pain, anxiety, and distress were obtained as well as an observed measure of distress. Samples were collected from children and biological parents for analysis of genomic variation. Genotyped variants had known or suspected association with phenotypes of interest. Analyses included child-only association and family-based transmission disequilibrium tests.

RESULTS

Genotype and phenotype data were available from 828 children and 376 family trios. Children were 50% male, had a mean age of 7.2 years, and were 84% White/non-Hispanic. In family-based analysis, one single-nucleotide polymorphism (SNP; rs1143629, interleukin ( IL1B) 1β) was associated with observed child distress at Bonferroni-corrected levels of significance ( p = .00013), while two approached significance for association with high state anxiety (rs6330 Nerve Growth Factor, Beta Subunit, [ NGFB]) and high trait anxiety (rs6265 brain-derived neurotrophic factor [ BDNF]). In the child-only analysis, multiple SNPs showed nominal evidence of relationships with phenotypes of interest. rs6265 BDNF and rs2941026 cholecystokinin B receptor had possible relationships with trait anxiety in child-only and family-based analyses.

CONCLUSIONS

Exploring genomic variation furthers our understanding of pain, anxiety, and distress and facilitates genomic screening to identify children at high risk of procedural pain, anxiety, and distress. Combined with clinical observations and knowledge, such explorations could help guide tailoring of interventions to limit procedure-related distress and identify genes and pathways of interest for future genotype-phenotype studies.

A generalized Defries-Fulker regression framework for the analysis of twin data

Twin studies compare the similarity between monozygotic twins to that between dizygotic twins in order to investigate the relative contributions of latent genetic and environmental factors influencing a phenotype. Statistical methods for twin data include likelihood estimation and Defries-Fulker regression. We propose a new generalization of the Defries-Fulker model that fully incorporates the effects of observed covariates on both members of a twin pair and is robust to violations of the Normality assumption. A simulation study demonstrates that the method is competitive with likelihood analysis. The Defries-Fulker strategy yields new insight into the parameter space of the twin model and provides a novel, prediction-based interpretation of twin study results that unifies continuous and binary traits. Due to the simplicity of its structure, extensions of the model have the potential to encompass generalized linear models, censored and truncated data; and gene by environment interactions.

The Twin Research Registry at SRI International

The Twin Research Registry (TRR) at SRI International is a community-based registry of twins established in 1995 by advertising in local media, mainly on radio stations and in newspapers. As of August 2012, there are 3,120 same- and opposite-sex twins enrolled; 86% are 18 years of age or older (mean age 44.9 years, SD 16.9 years) and 14% less than 18 years of age (mean age 8.9 years, SD 4.5); 67% are female, and 62% are self-reported monozygotic (MZ). More than 1,375 twins have participated in studies over the last 15 years in collaboration with the University of California Medical Center in San Francisco, the University of Texas MD Anderson Cancer Center, and the Stanford University School of Medicine. Each twin completes a registration form with basic demographic information either online at the TRR Web site or during a telephone interview. Contact is maintained with members by means of annual newsletters and birthday cards. The managers of the TRR protect the confidentiality of twin data with established policies; no information is given to other researchers without prior permission from the twins; and all methods and procedures are reviewed by an Institutional Review Board. Phenotypes studied thus far include those related to nicotine metabolism, mutagen sensitivity, pain response before and after administration of an opioid, and a variety of immunological responses to environmental exposures, including second-hand smoke and vaccination for seasonal influenza virus and Varicella zoster virus. Twins in the TRR have participated in studies of complex, clinically relevant phenotypes that would not be feasible to measure in larger samples.