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At least 91 records · Page 5Linked to original sources
PubMed2006

Characterizing variation in sex steroid hormone pathway genes in women of 4 races/ethnicities: the Study of Women's Health Across the Nation (SWAN).

This report characterizes genotypes and haplotypes in 6 genes (27 single nucleotide polymorphisms [SNPs]) from the Sex Steroid Hormone Genetics Protocol developed though the DNA Repository of the Study of Women's Health Across the Nation (SWAN) Genetics Study. The SWAN Genetics Study is a component of a longitudinal study describing health-related attributes of the menopausal transition in African American, Caucasian, Chinese, Hispanic, and Japanese women. At baseline, SWAN recruited menstruating women, aged 42 to 52 years, who were not using exogenous hormones. During the sixth and seventh years of the study, buccal cells in a mouthwash slurry and whole blood were collected for a DNA repository. Immortalized cell lines were created and genotyped in 1,538 specimens from 1,757 women who participated in the SWAN Genetics Study. DNA from those cells was genotyped for genes in the sex steroid hormone pathway. SNPs were evaluated for genotype and allele frequencies (and differences) according to race/ethnicity and haplotyped in anticipation of studying their associations with health-related measures. We demonstrated that allele frequencies differed significantly by race/ethnicity. There was substantial linkage disequilibrium among many of the SNPs and only a few SNPs showed significant Hardy-Weinberg disequilibrium within race/ethnicity. Finally, there are a number of haplotype patterns that vary according to race/ethnicity, including a "yin-yang" pattern for 17HSD among Caucasian, Chinese, and Japanese women, but not among African American women. Repository specimens developed in anticipation of genomic or metabolomics studies can extend the contribution of the parent study by developing hybrid strategies that support both SNP association studies as well as coarse and fine mapping to evaluate possible genomic locations of causal variants.

Adult↗
PubMed2026

Exploring genomic regions regulating the liver transcriptome and energy homeostasis in pigs.

In pigs, energy homeostasis has an impact on meat quality and health. In a Duroc pig population, 30 quantitative trait locus (QTL) regions associated with fatty acid (FA) composition in adipose tissue, plasma, liver and muscle were previously identified. Mapping of expression quantitative trait locus (eQTL) regions will provide a molecular hypothesis for genotype-phenotype interactions and may allow the identification of shared causal variants, key to increasing our understanding of the genetic regulation of FA composition and energy homeostasis. However, gene expression is impacted by environmental factors, while individual-level allelic imbalance (AI) can be more reliable and can be surveyed via allelic-specific expression (ASE) analysis. Furthermore, treatment of ASE as a quantitative trait allows the identification of allele-specific expression quantitative trait loci (aseQTLs), which are variants whose heterozygosity is linked to the AI of a nearby single-nucleotide polymorphism (SNP), pointing to regulatory elements. In this study, liver was selected as a key metabolic hub with an important role in the regulation of energy homeostasis, and 310 liver RNA sequencing samples were analysed using a combination of (1) eQTL mapping, (2) ASE analysis, and (3) aseQTL mapping methods. A total of 2 188 eQTL regions were identified, mostly cis-eQTL regions (73.17%). ASE analysis reported 1 964 ASE SNPs, associated with 633 genes. Finally, aseQTL mapping reported 64 172 aseQTL, associated with the AI of 31 genes. Colocalisation analysis combined with ASE analysis showed that the expression of FADS1 and FADS2 genes is associated with the polyunsaturated FA composition in several tissues, where microRNA regulation may be present. Finally, in the DGAT2 gene, annotated in a QTL region associated with multiple FAs in adipose tissue, ASE revealed allelic imbalance in the 3' untranslated region (UTR) of this gene. Allelic differential expression can be caused by a 13-bp insertion affecting messenger RNA stability, previously described, exemplifying how allelic imbalance is caused by a post-transcriptional regulatory mechanism undetectable by eQTL mapping. Furthermore, aseQTLs were associated with this gene, linked to a previously identified copy number variant not yet associated with DGAT2 expression. These results demonstrate how ASE analysis and aseQTL mapping can complement eQTL mapping, as they resolved a complex region affected by allelic heterogeneity, a main confounding effect of QTL mapping. In conclusion, the combination of eQTL mapping, ASE analysis and aseQTL mapping allowed the characterisation of the regulation of liver gene expression, improving our understanding of the genetic determinism of energy homeostasis.

Allele-specific expression↗
PubMed2026

Tonsillar expression quantitative trait loci verify and expand genetic contributors to childhood atopic diseases.

BACKGROUND: The spectrum of causal variants, mechanisms, and immunologic gene networks that influence pediatric atopic traits is not completely understood. Human genetic variation associated with transcript abundance (expression quantitative trait loci [eQTLs]) can help to advance our understanding, yet prior work has focused on profiling immune cell populations collected from peripheral blood primarily in adult populations, leaving tissue-resident lymphocytes collected from children uncharacterized. OBJECTIVE: We sought to characterize gene expression of 4 populations of tonsil-derived immune cell types collected from pediatric patients. METHODS: We collected naive B, germinal center B, naive T, and T follicular helper cells from the discarded tonsils of 103 children across development (age range 1-19). Following genotyping and RNA sequencing of samples, we performed differential expression and eQTL analysis, then statistically linked eQTL signals to relevant atopic traits via colocalization. RESULTS: We found differentially expressed genes across cell types and identified 13,393 expression genes (eGenes) (1,793 eGenes not previously reported in similar datasets) influenced by 27,603 eQTLs (5,199 eQTLs not previously reported). We linked eQTLs to associations identified in pediatric and adult asthma and atopy traits, nominating 78 eGenes including TRAF3, ZBTB10, and JAZF1 in disease-relevant cell types. CONCLUSIONS: Our freely available resource exemplifies the importance of discovery in native tissues and across human development.

Expression quantitative trait locus↗
PubMed2006

Breakthroughs in the search for dyslexia candidate genes.

Four genes have recently been proposed as candidates for dyslexia: dyslexia susceptibility 1 candidate 1 (DYX1C1), roundabout Drosophila homolog 1 (ROBO1), doublecortin domain-containing protein 2 (DCDC2) and KIAA0319. Each gene is implicated in global brain-development processes such as neural migration and axonal guidance, with the exception of DYX1C1, the function of which is still unknown. The most immediate clinical prospect of the discovery of these genes is the possibility of early identification of dyslexia via genetic screening. However, research efforts have yet to identify a functional mutation in any of these genes. When causal variants are identified, they will need to be considered within a multifactorial framework, which is likely to involve gene-gene and gene-environment interactions, to make accurate predictions of diagnostic status.

Axons↗
PubMed2026

Shared genetic architecture between major depression and intrinsic brain functional connectome organization.

BACKGROUND: Major depression (MD) is increasingly understood as a disorder characterized by widespread abnormalities in intrinsic brain functional network organization. Although both MD and brain functional connectome architecture are highly heritable, the genetic architecture underlying their relationship remains poorly characterized. METHODS: We integrated genome-wide association studies of MD with 191 ICA-based resting-state functional connectome traits to investigate their shared genetic architecture. These traits captured intrinsic connectome organization across amplitude, functional connectivity, and global connectivity domains. Cross-trait genetic analyses were used to assess pleiotropic overlap between traits. Locus-level and gene-based analyses integrating multi-omics evidence were performed to characterize the biological relevance of shared genetic signals. RESULTS: We identified significant genetic overlap between MD and 148 of 191 brain functional connectome traits. Cross-trait analyses revealed widespread shared genetic signals organized into 627 genomic loci across amplitude, functional connectivity, and global connectivity measures. Among these, 193 loci showed evidence consistent with shared causal variants based on colocalization analyses. Gene-level integration mapped these loci to 1459 protein-coding genes (390 unique genes). Multi-layer prioritization identified 17 high-confidence genes supported by convergent genomic, transcriptomic, and proteomic evidence, with enrichment in neurodevelopmental and lipid-related metabolism pathways. CONCLUSIONS: This study provides a multi-scale characterization of the shared genetic architecture between MD and intrinsic brain functional connectome organization, revealing that shared genetic signals between MD and brain functional systems are distributed across multiple functional levels and converge at the molecular level.

Connectome↗
PubMed2026

Mapping the Immune cell-specific gene regulatory network in bipolar disorder: A framework from scTWMR to exploratory drug-target annotation.

BACKGROUND: Although the involvement of the immune system in the genetic susceptibility of bipolar disorder (BD) is widely acknowledged, the causal relationship between gene expression in specific immune cell subtypes and BD requires systematic elucidation. METHODS: We implemented an analytical framework integrating single-cell transcriptome-wide Mendelian randomization (scTWMR) with colocalization analysis. This approach utilized cis-expression quantitative trait loci (cis-eQTLs) derived from 14 distinct immune cell types as instrumental variables to interrogate BD genome-wide association study (GWAS) summary statistics (comprising 41,917 cases and 371,549 controls). Subsequent investigations encompassed functional enrichment analysis, protein-protein interaction (PPI) network construction, phenome-wide association study (PheWAS), and performed an exploratory drug-target annotation. RESULTS: Our analysis identified 33 gene-immune cell associations. Colocalization analysis provided robust evidence (PPH4 > 90%) for shared causal variants implicating the MAD1L1, APOM, and NFKBIL1 loci. Significantly enriched biological pathways included cell cycle regulation, circadian rhythm entrainment, and neuroinflammation. The PPI network revealed a core regulatory module centered on histone-encoding and immune-related genes. Exploratory drug-target annotation nominated compounds for further investigation for compounds targeting APOM, TMEM258, and NFKBIL1. CONCLUSION: This study systematically delineates a genetically supported regulatory network of immune cell-specific gene expression in BD, predominantly implicating CD8⁺ effector T cells, plasma cells, and B cells. The findings corroborate established pathological pathways while uncovering novel cell type-specific therapeutic targets, thereby providing a genetic framework for prioritizing candidate targets for future investigation.

Bipolar disorder↗
PubMed2006

Genome-wide association mapping in bacteria?

Bacteria display many interesting phenotypes such as virulence, tissue specificity and host range, for which it would be useful to know the genetic basis. Association mapping involves identifying causal variants by showing that particular genotypes are statistically associated with a phenotypic trait in a sample of strains taken from a natural population. With the advent of high-throughput genotyping, association mapping is becoming an increasingly powerful approach. However, until recently, association studies had not been used in bacteria because of their strong population structure, which can produce false positives and/or loss of statistical power unless elucidated and taken into account in analyses. Here, we describe how association mapping could be successfully applied to bacteria and outline the necessary sampling and genotyping strategies.

Bacteria↗
PubMed2002

Haplotype diversity and the block structure of linkage disequilibrium.

Several recent studies indicate that patterns of linkage disequilibrium in the human genome cannot be reconciled with a uniform distribution of recombination events, but crossovers appear to be localized in short hot-spots that separate longer stretches of DNA. Markers within these low-recombination blocks show increased levels of linkage disequilibrium and very low haplotype diversity. This could simplify study of the genetic basis of complex diseases if causal variants are common.

Crossing Over, Genetic↗
PubMed2006

A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC.

The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and are essential in self versus non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune diseases. Yet identification of causal variants is problematic owing to linkage disequilibrium that extends across multiple HLA and non-HLA genes in the MHC. We therefore set out to characterize the linkage disequilibrium patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common SNPs and deletion-insertion polymorphisms across four population samples. The analysis provides informative tag SNPs that capture much of the common variation in the MHC region and that could be used in disease association studies, and it provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.

Genetic Predisposition to Disease↗
PubMed2006

Natural selection on human microRNA binding sites inferred from SNP data.

A fundamental problem in biology is understanding how natural selection has shaped the evolution of gene regulation. Here we use SNP genotype data and techniques from population genetics to study an entire layer of short, cis-regulatory sites in the human genome. MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally repress mRNA through cis-regulatory sites in 3' UTRs. We show that negative selection in humans is stronger on computationally predicted conserved miRNA binding sites than on other conserved sequence motifs in 3' UTRs, thus providing independent support for the target prediction model and explicitly demonstrating the contribution of miRNAs to darwinian fitness. Our techniques extend to nonconserved miRNA binding sites, and we estimate that 30%-50% of these are functional when the mRNA and miRNA are endogenously coexpressed. As we show that polymorphisms in predicted miRNA binding sites are likely to be deleterious, they are candidates for causal variants of human disease. We believe that our approach can be extended to studying other classes of cis-regulatory sites.

3' Untranslated Regions↗
PubMed2005

Association of the CTLA-4 gene with rheumatoid arthritis in Chinese Han population.

Cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) is important for downregulation of T-cell activation, and CTLA-4 gene polymorphisms have been implicated as risk factors for rheumatoid arthritis (RA). Previous studies of the association between the +49 polymorphism of the CTLA-4 gene in RA have provided conflicting results. In order to determine association of the CTLA-4 gene with RA in Chinese Han population, we used denaturing gradient gel electrophoresis (DGGE) to genotype polymorphisms of four SNPs (MH30, +49, CT60 and JO31) of the CTLA-4 gene in 326 RA patients and 250 healthy controls. Furthermore, meta-analysis of all available studies relating +49 polymorphism to the risk of RA was performed to confirm the disease association. Among the SNPs examined, the genotype frequencies of CTLA-4 +49 and CT60 in RA patients differed significantly from controls (P=0.028 and 0.007). In addition, the distribution of four haplotypes constructed by these two SNPs was significantly different between patients and controls (chi(2)=10.58, d.f. =3, P=0.014). The meta-analysis also revealed that in both European and Asian populations, the CLTA-4 +49 G allele was associated with the risk of RA. These results suggested that the CTLA-4 gene might be involved in the susceptibility to RA in the Chinese Han population and both +49 and CT60 of CTLA-4 gene might be the causal variants in RA disease.

3' Untranslated Regions↗
PubMed2006

Haplotypes in the CTLA4 region are associated with coeliac disease in the Irish population.

Chromosomal region 2q33 encodes the immune regulatory genes, CTLA4, ICOS and CD28, which are involved in regulation of T-cell activity and has been studied as a candidate gene locus in autoimmune diseases, including coeliac disease (CD). We have investigated whether an association exists between this region and CD in the Irish population using a comprehensive analysis for genetic variation. Using a haplotype-tagging approach, this gene cluster was investigated for disease association in a case-control study comprising 394 CD patients and 421 ethnically matched healthy controls. Several SNPs, including CTLA4_CT60, showed association with disease; however, after correction for multiple-testing, CTLA4-658C/T was the only polymorphism found to show significant association with disease when allele, genotype, or carrier status frequency were analysed (carrier status (Allele C), P = 0.0016). Haplotype analysis revealed a haplotype incorporating the CD28/CTLA4 and two 5' ICOS polymorphisms to be significantly associated with disease (patients 24.1%; controls 31.5%; P = 0.035), as was a shorter haplotype composed of the CTLA4 markers only (30.9 vs 34.9%; P = 0.042). The extended haplotype incorporating CD28/CTLA4 and 5' ICOS is more strongly associated with disease than haplotypes of individual genes. This suggests a causal variant associated with this haplotype may be associated with disease in this population.

Antigens, CD↗
PubMed2005

Genetic association studies in complex disease: disentangling additional predisposing loci from associated neutral loci using a constrained - permutation approach.

In the process of genetically mapping a complex disease, the question may arise whether a certain polymorphism is the only causal variant in a region. A number of methods can answer this question, but unfortunately these methods are optimal for bi-allelic loci only. We wanted to develop a method that is more suited for multi-allelic loci, such as microsatellite markers. We propose the Additional Disease Loci Test (ADLT): the alleles at an additional locus are permuted within the subsample of haplotypes that have identical alleles at the predisposing locus. The hypothesis being tested is, whether the predisposing locus is the sole factor predisposing to the trait that is in LD with the additional locus under study. We applied ADLT to simulated datasets and a published dataset on Type 1 Diabetes, genotyped for microsatellite markers in the HLA-region. The method showed the expected number of false-positive results in the absence of additional loci, but proved to be more powerful than existing methods in the presence of additional disease loci. ADLT was especially superior in datasets with less LD or with multiple predisposing alleles. We conclude that the ADLT can be useful in identifying additional disease loci.

Diabetes Mellitus, Type 1↗
PubMed2026

The Inflammation-Thrombosis Genetic Axis in Abdominal Aortic Aneurysm: A Shared Roadmap to Precision Medicine.

Abdominal Aortic Aneurysm (AAA) is characterized by persistent inflammation, extracellular matrix loss, and intraluminal thrombus formation, yet the genetic links among these processes remain incompletely defined. Here, we examine evidence that genetic variation can influence inflammatory and thrombotic responses at the same time. Findings from genome-wide association studies are considered alongside transcriptomic, proteomic, single-cell, epigenetic, and experimental data. Particular attention is given to candidate genes and signaling networks relevant to AAA susceptibility, enlargement, and rupture. The available evidence supports a model in which inherited susceptibility alters the balance between vascular inflammation, coagulation, fibrinolysis, and wall repair. However, many reported loci still lack functional confirmation, and most genetic data come from populations of European ancestry. Defining the causal variants and the cells in which they act will be necessary before these findings can be used for individualized screening or treatment.

abdominal aortic aneurysm↗
PubMed2003

Association of multidrug resistance in epilepsy with a polymorphism in the drug-transporter gene ABCB1.

BACKGROUND: One third of patients with epilepsy have drug-resistant epilepsy, which is associated with an increased risk of death and debilitating psychosocial consequences. Because this form is resistant to multiple antiepileptic drugs, the mode of resistance must be nonspecific, involving drug-efflux transporters such as ATP-binding cassette sub-family B member 1 (ABCB1, also known as MDR1 and P-glycoprotein 170). We hypothesized that the CC genotype at the ABCB1 C3435T polymorphism, which is associated with increased expression of the protein, influences the response to antiepileptic-drug treatment. METHODS: ABCB1 3435 was genotyped in 315 patients with epilepsy, classified as drug-resistant in 200 and drug-responsive in 115, and 200 control subjects without epilepsy. Recently devised methods were used to control for population stratification, and linkage disequilibrium was calculated across the gene. RESULTS: As compared with patients with drug-responsive epilepsy, patients with drug-resistant epilepsy were more likely to have the CC genotype at ABCB1 3435 than the TT genotype (odds ratio, 2.66; 95 percent confidence interval, 1.32 to 5.38; P=0.006). There was no genetic stratification between the two groups of patients. The polymorphism fell within an extensive block of linkage disequilibrium spanning much or all of the gene, implying that the polymorphism may not itself be causal but rather may be linked with the causal variant. CONCLUSIONS: These pharmacogenomic results identify a genetic factor associated with resistance to antiepileptic drugs.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2005

Localization of a type 1 diabetes locus in the IL2RA/CD25 region by use of tag single-nucleotide polymorphisms.

As part of an ongoing search for genes associated with type 1 diabetes (T1D), a common autoimmune disease, we tested the biological candidate gene IL2RA (CD25), which encodes a subunit (IL-2R alpha) of the high-affinity interleukin-2 (IL-2) receptor complex. We employed a tag single-nucleotide polymorphism (tag SNP) approach in large T1D sample collections consisting of 7,457 cases and controls and 725 multiplex families. Tag SNPs were analyzed using a multilocus test to provide a regional test for association. We found strong statistical evidence in the case-control collection (P=6.5x10(-8)) for a T1D locus in the CD25 region of chromosome 10p15 and replicated the association in the family collection (P=7.3x10(-3); combined P=1.3x10(-10)). These results illustrate the utility of tag SNPs in a chromosome-regional test of disease association and justify future fine mapping of the causal variant in the region.

Case-Control Studies↗
PubMed2006

Coverage and power in genomewide association studies.

The ability of genomewide association studies to decipher genetic traits is driven in part by how well the measured single-nucleotide polymorphisms "cover" the unmeasured causal variants. Estimates of coverage based on standard linkage-disequilibrium measures, such as the average maximum squared correlation coefficient (r2), can lead to inaccurate and inflated estimates of the power of genomewide association studies. In contrast, use of the "cumulative r2 adjusted power" measure presented here gives more-accurate estimates of power for genomewide association studies.

Chromosome Mapping↗
PubMed2026

Integrated multi-omics strategies for identifying novel therapies in psoriasis.

MOTIVATION: Psoriasis is a chronic, immune-mediated disorder with an unmet need for effective treatments. To systematically prioritize therapeutic targets, we integrated proteome-wide Mendelian randomization (MR) with expression validation in blood/skin, genetic susceptibility analysis, differential gene expression (DGE) from bulk and single-cell RNA sequencing (scRNA-seq), colocalization, pathway enrichment, and protein-protein interaction analyses. RESULTS: Proteome-wide MR identified 29 candidate protein targets (Bonferroni-corrected), all replicated in independent datasets. Fifteen targets showed significant expression associations in blood or skin. Eleven proteins-UBLCP1, IL23A, ASF1A, RARRES2, ICAM1, PRSS53, ICAM5, GCA, IL2RA, DBI, and NFKB1-exhibited consistent directional effects with their genes. Genetic susceptibility analysis confirmed 20 target-specific polygenic scores for psoriasis and five for psoriatic arthritis. DGE analysis identified 13 targets in bulk and 13 in scRNA-seq-primarily in keratinocytes and immune cells-with IL2RA, COMP, and A2ML1 dysregulated across both. Colocalization analysis implicated shared causal variants for psoriasis in ASF1A, CD8A, CTF1, IL7R, MMP12, RARRES2, XCL2, DBI, IL23A, IL2RA, SGSH, and TIMD4. Enrichment analyses highlighted involvement in cytotoxicity, immune regulation, and JAK-STAT signaling. Eighteen targets interacted with approved anti-psoriasis drugs. Notably, drugs targeting IL2RA, IL7R, CTF1, ICAM1, MMP12, NFKB1, CD8A, DDX58, IL12A, SGSH, and FAP are approved or in trials for other diseases, suggesting repurposing potential. Our integrative multi-omics approach prioritized 29 high-confidence targets, including 13 novel candidates (RARRES2, ASF1A, CTF1, DBI, B3GNT2, CD8A, TIMD4, CRTAM, SGSH, XCL2, DAPK2, A2ML1, and FAP). Several high-priority targets-such as IL2RA, IL23, MMP12, RARRES2, IL7R, and ICAM1-were supported across analytical layers. These findings provide a robust foundation for psoriasis drug development. AVAILABILITY AND IMPLEMENTATION: The code used for the analyses in this manuscript has been archived in Zenodo at [DOI: 10.5281/zenodo.19692128].

Psoriasis↗