A sex-specific microRNA-96/5HT1B Axis influences development of pulmonary hypertension

Rationale: Females are predisposed to pulmonary arterial hypertension (PAH); evidence suggests that serotonin, mutations in the bone morphogenetic protein receptor (BMPR) II gene, and estrogens influence development of PAH. The 5-hydroxytryptamine 1B receptor (5-HT1BR) mediates human pulmonary artery smooth muscle cell (hPASMC) proliferation. Objectives: We aimed to determine whether selected microRNAs (miRNAs) expressed in PASMCs are influenced by sex, BMPR-II mutations, and estrogens, and contribute to PASMC proliferation in PAH. Methods: Expression levels of miRNAs targeting genes related to PAH, estrogen, and serotonin were determined by quantitative RT-PCR in hPASMCs and mouse PASMCs harboring a heterozygous mutation in BMPR-II (BMPR-IIR899X+/− PASMCs). miRNA-96 targets 5-HT1BR and was selected for further investigation. miRNA target validation was confirmed by luciferase reporter assay. Precursor miRNA-96 was transfected into hPASMCs to examine effects on proliferation and 5-HT1BR expression. The effect of a miRNA-96 mimic on the development of hypoxic pulmonary hypertension in mice was also assessed. Measurements and Main Results: miRNA-96 expression was reduced in BMPR-IIR899X+/− PASMCs from female mice and hPASMCs from female patients with PAH; this was associated with increased 5-HT1BR expression and serotonin-mediated proliferation. 5-HT1BR was validated as a target for miRNA-96. Transfection of precursor miRNA-96 into hPASMCs reduced 5-HT1BR expression and inhibited serotonin-induced proliferation. Restoration of miRNA-96 expression in pulmonary arteries in vivo via administration of an miRNA-96 mimic reduced the development of hypoxia-induced pulmonary hypertension in the mouse. Conclusions: Increased 5-HT1BR expression may be a consequence of decreased miRNA-96 expression in female patient PASMCs, and this may contribute to the development of PAH

Genetic and Psychological Factors Interact to Predict Physical Impairment Phenotypes Following Exercise-Induced Shoulder Injury

Background: We investigated interactions between genetic and psychological factors in predicting shoulder impairment phenotypes. We hypothesized that pro-inflammatory genes would display stronger relationships compared with pain-related genes when combined with psychological factors for predicting phenotypic changes.Subjects and methods: Altogether, 190 participants completed a 5-day experimental protocol. An experimental shoulder injury model was used to induce physical impairment, and a priori selected genetic (pain-related, pro-inflammatory) and psychological (anxiety, depressive symptoms, pain catastrophizing, fear of pain, kinesiophobia) factors were included as predictors of interest. Impairment phenotypes were injury-induced deficits in range of motion (ROM) and strength. After controlling for age, sex, and race, genetic and psychological predictors were entered separately as main effects and interaction terms in regression models for each phenotype.Results: Strong statistical evidence was provided for interactions between: 1) IL-1β (rs1143634) and fear of pain for predicting loss of shoulder flexion and abduction, 2) IL-1β (rs1143634) and anxiety for predicting loss of flexion, and 3) IL-1β (rs1143634) and depressive symptoms for predicting loss of internal rotation. In addition, the interaction between OPRM1 (rs1799971) and fear of pain as well as COMT (rs4818) and pain catastrophizing provided strong statistical evidence for predicting strength loss.Conclusion: Pro-inflammatory gene variants contributed more to physical impairment with two single nucleotide polymorphisms (SNPs; IL-1β [rs1143634] and TNF/LTA [rs2229094]) interacting with psychological factors to predict six shoulder impairment phenotypes. In comparison, two pain-related gene SNPs (OPRM1 [rs1799971] and COMT [rs4818]) interacted with psychological factors to predict four shoulder impairment phenotypes (abduction: 5-day average loss; strength loss: 5-day average, peak, and relative loss)

A computational model for sex-specific genetic architecture of complex traits in humans: Implications for mapping pain sensitivity

Understanding differences in the genetic architecture of complex traits between the two sexes has significant implications for evolutionary studies and clinical diagnosis. However, our knowledge about sex-specific genetic architecture is limited largely because of a lack of analytical models that can detect and quantify the effects of sex on the complexity of quantitative genetic variation. Here, we derived a statistical model for mapping DNA sequence variants that contribute to sex-specific differences in allele frequencies, linkage disequilibria, and additive and dominance genetic effects due to haplotype diversity. This model allows a genome-wide search for functional haplotypes and the estimation and test of haplotype by sex interactions and sex-specific heritability. The model, validated by simulation studies, was used to detect sex-specific functional haplotypes that encode a pain sensitivity trait in humans. The model could have important implications for mapping complex trait genes and studying the detailed genetic architecture of sex-specific differences

Modeling genetic imprinting effects of DNA sequences with multilocus polymorphism data

Single nucleotide polymorphisms (SNPs) represent the most widespread type of DNA sequence variation in the human genome and they have recently emerged as valuable genetic markers for revealing the genetic architecture of complex traits in terms of nucleotide combination and sequence. Here, we extend an algorithmic model for the haplotype analysis of SNPs to estimate the effects of genetic imprinting expressed at the DNA sequence level. The model provides a general procedure for identifying the number and types of optimal DNA sequence variants that are expressed differently due to their parental origin. The model is used to analyze a genetic data set collected from a pain genetics project. We find that DNA haplotype GAC from three SNPs, OPRKG36T (with two alleles G and T), OPRKA843G (with alleles A and G), and OPRKC846T (with alleles C and T), at the kappa-opioid receptor, triggers a significant effect on pain sensitivity, but with expression significantly depending on the parent from which it is inherited (p = 0.008). With a tremendous advance in SNP identification and automated screening, the model founded on haplotype discovery and statistical inference may provide a useful tool for genetic analysis of any quantitative trait with complex inheritance

Rapid in vivo measurement of B-amyloid reveals biphasic clearance kinetics in an Alzheimer\u27s mouse model

Accumulation of ?-amyloid peptide is a key step in Alzheimer?s disease pathogenesis. Yuede et al. propose a novel method to track ?-amyloid levels in vivo

Localization of a human T-cell-specific gene, RANTES (D17S136E), to chromosome 17q11.2-q12

We report here the localization of the gene for a human T-cell-specific molecule, designated RANTES, to human chromosome region 17q11.2-q12 by in situ hybridization and analysis of somatic cell hybrids using a cDNA probe to the gene. We have recently shown that this gene, which encodes a small, secreted, putative lymphokine, is a member of a larger gene family some of whose members reside on chromosome 4 but most of whose members have not to date been mapped. A secondary hybridization peak was noted on the region of human chromosome 5q31-q34, which may represent the location of other members of the gene family. Interestingly, this latter region overlaps with the location of an extended linked cluster of growth factor and receptor genes, some of which may be coregulated with members of the RANTES gene family.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28717/1/0000538.pd

Variant of TYR and Autoimmunity Susceptibility Loci in Generalized Vitiligo.

BACKGROUND Generalized vitiligo is an autoimmune disease characterized by melanocyte loss, which results in patchy depigmentation of skin and hair, and is associated with an elevated risk of other autoimmune diseases. METHODS To identify generalized vitiligo susceptibility loci, we conducted a genomewide association study. We genotyped 579,146 single-nucleotide polymorphisms (SNPs) in 1514 patients with generalized vitiligo who were of European-derived white (CEU) ancestry and compared the genotypes with publicly available control genotypes from 2813 CEU persons. We then tested 50 SNPs in two replication sets, one comprising 677 independent CEU patients and 1106 CEU controls and the other comprising 183 CEU simplex trios with generalized vitiligo and 332 CEU multiplex families. RESULTS We detected significant associations between generalized vitiligo and SNPs at several loci previously associated with other autoimmune diseases. These included genes encoding major-histocompatibility-complex class I molecules (P=9.05×10−23) and class II molecules (P=4.50×10−34), PTPN22 (P=1.31×10−7), LPP (P=1.01×10−11), IL2RA (P=2.78×10−9), UBASH3A (P=1.26×10−9), and C1QTNF6 (P=2.21×10−16). We also detected associations between generalized vitiligo and SNPs in two additional immune-related loci, RERE (P=7.07×10−15) and GZMB (P=3.44×10−8), and in a locus containing TYR (P=1.60×10−18), encoding tyrosinase. CONCLUSIONS We observed associations between generalized vitiligo and markers implicating multiple genes, some associated with other autoimmune diseases and one (TYR) that may mediate target-cell specificity and indicate a mutually exclusive relationship between susceptibility to vitiligo and susceptibility to melanoma

Common variants in FOXP1 are associated with generalized vitiligo

In a recent genome-wide association study of generalized vitiligo, we identified ten confirmed susceptibility loci. By testing additional loci that showed suggestive association in the genome-wide study, using two replication cohorts of European descent, we observed replicated association of generalized vitiligo with variants at 3p13 encompassing FOXP1 (rs17008723, combined P = 1.04 × 10−8) and with variants at 6q27 encompassing CCR6 (rs6902119, combined P = 3.94 × 10−7)