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PubMed2025

Genetic pleiotropy underlying obesity and autoimmune disorders: a large-scale cross-trait gwas analysis in European ancestry populations.

BACKGROUND: Obesity and autoimmune disorders represent a significant comorbidity burden, yet their shared genetic architecture is not fully understood. Elucidating the pleiotropic genetic basis underlying both conditions is crucial for unraveling the mechanisms driving their co-occurrence and advancing therapeutic strategies. METHODS: We conducted a large-scale cross-trait analysis integrating genome-wide association study (GWAS) summary data for obesity and 17 autoimmune diseases. Genetic correlations were assessed using LD score regression and high-definition likelihood. Cross-trait pleiotropic analysis was performed using Stratified Pleiotropic Locus Mapping (PLACO) to identify shared loci, followed by Bayesian colocalization to confirm shared causal variants. Gene-level and tissue-specific heritability analyses were conducted, and drug targets were prioritized via summary-based Mendelian randomization (SMR). Finally, immune co-localization and bidirectional Mendelian randomization were employed to elucidate immunological mechanisms and causal relationships. RESULTS: Our analysis identified eight autoimmune diseases with significant genetic correlations to obesity. We discovered 10,324 pleiotropic SNPs, which mapped to 52 independent risk loci, with nine loci confirmed as shared causal variants by colocalization. Gene-level analysis revealed 133 unique pleiotropic genes, including CLN3, SH2B1, and MMEL1, enriched in pathways of hematopoietic cell differentiation and immune homeostasis. Tissue-specific heritability was most prominent in the spleen, whole blood, and EBV-transformed lymphocytes. Immuno-co-localization implicated six IgD+ CD38- %B cell-related traits as key pathological conduits. Bidirectional Mendelian randomization established a causal role of obesity in hypothyroidism, psoriasis, and multiple sclerosis, while revealing an inverse causal association of type 1 diabetes with obesity risk. CONCLUSIONS: This study demonstrates a robust shared genetic foundation between obesity and multiple autoimmune diseases, pinpointing specific pleiotropic loci, genes, and immune cell subsets. Our findings provide a mechanistic framework for their comorbidity and highlight potential targets for therapeutic intervention.

Humans↗

PubMed2006

Direct or indirect association in a complex disease: the role of SLC22A4 and SLC22A5 functional variants in Crohn disease.

A common haplotype spanning 250 kb on chromosome 5q31 is strongly associated with Crohn disease (CD). Recently, two functional variants within the SLC22A4 and SLC22A5 genes at this locus (IBD5), L503F (c.1507C > T) and G-207C (c.-207G > C), have been proposed to contribute directly to susceptibility to CD. However, extensive linkage disequilibrium at the IBD5 locus has complicated efforts to distinguish causal variants from association of the general risk haplotype. We genotyped the SLC22A4 and SLC22A5 variants and other polymorphisms across the risk haplotype in four populations of European origin, and applied regression-based haplotype analysis to over 1,200 fully genotyped case-control pairs, modeling case/control status on the presence of one or more SNPs to test for conditional association and to identify risk haplotypes. We found highly significant association of SNPs at the IBD5 locus with Crohn disease in all populations tested. However, the frequencies of L503F and G-207C in individuals who did not carry the general IBD5 risk haplotype were not significantly different in cases and controls, with associated disease odds ratios (ORs) of 0.90 (95% CI, 0.57-1.40) and 0.90 (95% CI, 0.65-1.23), respectively. Haplotype analysis showed that addition of the SLC22A4 and SLC22A5 variants to a null model that included the background risk haplotype did not significantly improve the model fit. In addition to the common risk haplotype, several rare haplotypes had an increased frequency in cases compared to controls. This study suggests that the molecular basis for Crohn disease susceptibility at the IBD5 locus remains to be defined, and highlights the challenge of the identification of causal variants in a complex disease in regions of extensive linkage disequilibrium.

Case-Control Studies↗

PubMed2006

OCTNs: will the real IBD5 gene please stand up?

Crohn's disease and ulcerative colitis are inflammatory disorders of the gastrointestinal tract with a substantial heritable component. The IBD5 region on chromosome 5q31 is one of only two loci widely confirmed to be associated with Crohn's disease in multiple independent cohorts. Although many populations have demonstrated association with IBD5, there remains uncertainty as to the causal variant within the region. A recent report identified polymorphisms in SLC22A4 (OCTN1) and SLC22A5 (OCTN2) as being responsible for the IBD5 association, however, these findings have not been replicated. This review discusses the data evaluating the IBD5 locus and the OCTN genes and their relationship to inflammatory bowel disease. Several other genes, including IRF1 and P4HA2 may be equally as likely to contain the IBD5 causal variant as the OCTN genes.

Colitis, Ulcerative↗

PubMed2025

Circulating inflammatory proteins and osteomyelitis: A bidirectional Mendelian randomization and colocalization analysis.

Circulating inflammatory proteins (CIPs) have been implicated in the progression of osteomyelitis (OM); however, whether these proteins play a causal role or are merely a consequence remains unclear. This study aimed to assess the causal relationships between CIPs and OM using a bidirectional 2-sample Mendelian randomization (MR) approach. MR analyses were performed using genome-wide association study summary statistics for 91 inflammation-related proteins (n = 14,824) and OM (1881 cases and 3,91,037 controls). The inverse variance weighted method was used as the primary analytical approach, supplemented by MR-Egger, weighted median, simple mode, and weighted mode methods. Sensitivity analyses were conducted to evaluate heterogeneity, horizontal pleiotropy, and robustness. Colocalization analysis was applied to identify shared causal variants, and pathway enrichment analysis was used to explore underlying biological mechanisms. Forward MR analysis revealed that elevated levels of tumor necrosis factor-beta (TNF-β) were significantly associated with increased OM risk (odds ratio [OR] = 1.132; 95% confidence interval [CI]: 1.052-1.217; false discovery rate [FDR] = 0.027). Conversely, decreased levels of osteoprotegerin (OR = 0.772; 95% CI: 0.671-0.889; FDR = 0.015) and adenosine deaminase (OR = 0.811; 95% CI: 0.736-0.894; FDR < 0.001) were associated with increased OM risk. Reverse MR analysis identified increased levels of interleukin-15 receptor alpha, C-X-C motif chemokine ligand 1, fms-related tyrosine kinase 3 ligand, interleukin-20, interleukin-10 (IL10), C-C motif chemokine ligand 19, and CXCL6 as being significantly associated with OM susceptibility (all FDR < 0.05). Colocalization analysis provided strong evidence for a shared causal variant between TNF-β and OM (posterior probability for hypothesis 4 = 0.999). Enrichment analyses indicated involvement of implicated proteins in Toll-like receptor signaling and T-helper 17 cell differentiation pathways. This study identified several CIPs - including TNF-β, osteoprotegerin, and adenosine deaminase - as potentially causal in OM development. These findings highlight promising targets for future immunomodulatory therapies aimed at preventing or mitigating osteomyelitis.

Humans↗

PubMed2004

Bayesian association-based fine mapping in small chromosomal segments.

A Bayesian method for fine mapping is presented, which deals with multiallelic markers (with two or more alleles), unknown phase, missing data, multiple causal variants, and both continuous and binary phenotypes. We consider small chromosomal segments spanned by a dense set of closely linked markers and putative genes only at marker points. In the phenotypic model, locus-specific indicator variables are used to control inclusion in or exclusion from marker contributions. To account for covariance between consecutive loci and to control fluctuations in association signals along a candidate region we introduce a joint prior for the indicators that depends on genetic or physical map distances. The potential of the method, including posterior estimation of trait-associated loci, their effects, linkage disequilibrium pattern due to close linkage of loci, and the age of a causal variant (time to most recent common ancestor), is illustrated with the well-known cystic fibrosis and Friedreich ataxia data sets by assuming that haplotypes were not available. In addition, simulation analysis with large genetic distances is shown. Estimation of model parameters is based on Markov chain Monte Carlo (MCMC) sampling and is implemented using WinBUGS. The model specification code is freely available for research purposes from http://www.rni.helsinki.fi/~mjs/.

Algorithms↗

PubMed2025

Genomic structural equation modeling elucidates the shared genetic architecture of allergic disorders.

BACKGROUND: The intricate shared genetic architecture underlying allergic disorders-including allergic asthma, atopic dermatitis, contact dermatitis, allergic rhinitis, allergic conjunctivitis, allergic urticaria, anaphylaxis, and eosinophilic esophagitis-remains incompletely characterized. METHODS: Our study employed genomic structural equation modeling (Genomic SEM) to define the common factor representing the shared genetic architecture of allergic disorders. Coupled with diverse post-GWAS analytical methods, we aimed to discover susceptible loci and investigate genetic associations with external traits. Furthermore, we explored enriched genetic pathways, cellular layers, and genomic elements, and investigated putative plasma protein biomarkers. Polygenic risk score (PRS) analyses, leveraging our integrated GWAS data, were conducted to assess chromosomal-level risk associations for allergic disorders. RESULTS: A well-fitted genomic SEM integrated GWAS data, revealing the shared genetic architecture of allergic disorders. We identified a total of 2038 genome-wide significant SNP loci (p < 5e-8), including 31 previously unreported loci. Fine-mapping of variants and gene sets pinpointed 2 causal variants and 31 candidate susceptible genes. Genetic correlation analyses further illuminated the shared genetic architecture underlying multiple traits, notably psychiatric disorders. Preliminary findings identified four putative causal plasma protein biomarkers. CONCLUSION: Notably, this study presents the first comprehensive genetic characterization of allergic disorders through a GWAS analysis of an unmeasured composite phenotype, providing novel insights into shared etiological pathways across these conditions.

Humans↗

PubMed2026

Post-genome-wide association study variant-to-function challenges in asthma research.

Genome-wide association studies of asthma have identified nearly 200 independent loci, yet the mechanisms through which individual loci influence asthma risk remain largely unknown. A growing array of computational and experimental tools has begun to fill these gaps by identifying causal variants and effector genes and characterizing their functions. In parallel, emerging studies are exploring the translational applications of genetic and multiomics data in asthma, including defining molecular endotypes and predicting disease risk. Here we review the strengths and limitations of current approaches for addressing the post-genome-wide association study challenges and discuss the next tier of questions and directions for the field.

Humans↗

PubMed2003

The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies.

Understanding of brain functioning requires the investigation of activated cortical networks, in particular the detection of interactions between different cortical sites. Commonly, coherence and correlation are used to describe interrelations between EEG signals. However, on this basis, no statements on causality or the direction of their interrelations are possible. Causality between two signals may be expressed in terms of upgrading the predictability of one signal by the knowledge of the immediate past of the other signal. The best-established approach in this context is the so-called Granger causality. The classical estimation of Granger causality requires the stationarity of the signals. In this way, transient pathways of information transfer stay hidden. The study presents an adaptive estimation of Granger causality. Simulations demonstrate the usefulness of the time-variant Granger causality for detecting dynamic causal relations within time intervals of less than 100 ms. The time-variant Granger causality is applied to EEG data from the Stroop task. It was shown that conflict situations generate dense webs of interactions directed from posterior to anterior cortical sites. The web of directed interactions occurs mainly 400 ms after the stimulus onset and lasts up to the end of the task.

Adult↗

PubMed2026

Integrating multi-ancestry common and rare variant mapping accelerates therapeutic target discovery.

Integrating human genetics into therapeutic discovery accelerates drug development. However, ancestral biases in historical cohorts have left critical functional variation largely uncharted. Here, we leverage the diverse NIH All of Us Research Program to conduct comprehensive common- and rare-variant association analyses for 624 quantitative traits across 369,655 ancestrally diverse individuals. We identified 6,181 genome-wide significant locus-trait associations (526 novel) and 416 gene-trait associations (105 novel) via rare-variant burden testing. By integrating fine-mapping with computational variant-effect predictors, we systematically prioritized rare, likely causal variants driving these signals. Jointly modeling common and rare variation with protein-class annotations significantly improved the identification of known drug targets compared to common-variant analysis alone. Notably, we identified NRG4 as a high-confidence candidate therapeutic target for preserving kidney function. Our findings demonstrate that characterization of rare and common variation across diverse populations enhances causal gene discovery and identifies novel, actionable therapeutic targets.

Journal Article↗

PubMed2025

A Multi-omics Exploration Revealing SLIT2 as a Prime Therapeutic Target for Peripheral Facial Paralysis: Integrating Single-Cell Transcriptomics and Plasma Proteome Data.

Peripheral facial paralysis (PFP) is a common neurological disorder characterized by facial-nerve dysfunction. Identifying therapeutic targets and understanding the molecular and cellular mechanisms underlying PFP are crucial for developing effective treatment strategies. This study combined Mendelian randomization (MR) analysis and single-cell RNA sequencing (scRNA-seq) to explore potential therapeutic candidates and their roles in PFP pathophysiology. The MR analysis included 1925 publicly available plasma protein cis-heritability instruments. Instrumental variables were selected for MR analysis to identify plasma proteins associated with PFP, followed by colocalization analysis to evaluate shared genetic variants between the identified proteins and PFP. After the initial identification of plasma proteins associated with Bell's palsy using MR analysis, a rat model of facial-nerve injury was established to further dissect underlying mechanisms at cellular and molecular levels. Using scRNA-seq technology, we delved deeply into cellular Heterogeneity and dynamic changes in gene expression in the facial-nerve nucleus tissues under both injured and control conditions, thereby achieving a systematic study ranging from macroscopic genetic associations to microscopic cellular functions. Finally, expression patterns were preliminarily validated by performing in vitro immunofluorescence analysis on the facial-nerve nucleus samples of SD rats. The MR analysis results identified 30 plasma proteins significantly associated with PFP, with nine target genes showing differential expression in the scRNA-seq data. Colocalization analysis demonstrated that slit guidance Ligand 2 (SLIT2), semaphorin 4D (SEMA4D), EGF containing fibulin extracellular matrix protein 1 (EFEMP1), and sprouty related EVH1 domain containing 2 (SPRED2) shared causal variants with PFP. SLIT2 was highly expressed in the microglia and inhibitory neurons in the experimental group, whereas SEMA4D showed elevated expression across multiple glial cell types in the same group. In contrast, EFEMP1 and SPRED2 showed distinct expression patterns in fibroblasts and oligodendrocytes. The role of SLIT2 has been previously well-documented in many central nervous system diseases. However, for the first time, this study detected SLIT2 alteration after facial-nerve injury. Altered intercellular signaling, particularly enhanced SLIT2-ROBO signaling between neurons and glial cells, was observed in the PFP group. Pseudotime analysis revealed dynamic SLIT2 expression during microglia and inhibitory neuron differentiation, mirroring changes in ROBO1 expression. Immunofluorescence analysis of rat facial-nerve nucleus samples verified that SLIT2 protein levels were significantly increased in the facial-nerve nuclei of injured samples. In conclusion, despite the fact that this study is primarily founded on animal models and despite notable differences existing between animals and humans in terms of the facial motor nucleus, this study successfully identified SLIT2 as potential therapeutic targets for PFP. The SLIT2-ROBO axis stands out as a particularly promising candidate. SLIT2 may play a role in modulating neuroimmune interactions and promoting nerve repair. These findings provide a foundation for future clinical studies and targeted interventions to enhance recovery from PFP. Future research should focus on human sample validation to enhance clinical translation.

Animals↗

PubMed2006

The current status of association studies in obsessive-compulsive disorder.

During the last 2 decades, a large number of association studies have been dedicated to disentangling the genetic components that may be involved in the etiology of OCD. The preliminary and frequently in consistent nature of the data represented in the majority of OCD psychiatric genetic-association studies may seem discouraging. Failure to replicate, and thus to confirm, previously identified susceptibility loci could result from a number of reasons, including the potential for population admixture, the clinical heterogeneity of OCD, small sample sizes (and subsequent lack of power),publication bias, epistasis, or failure to account for multiple testing. Various methods of accounting for these confounders do exist and should be implemented in any genetic-association study that is to be regarded as robust and replicable. Discrepancy between results, however, might be ascribed to the underlying genetic differences between the populations in the respective studies (ie, the investigated variant may be in linkage disequilibrium with the causal variant in one population but not in another). Such discrepancies are difficult to reconcile in single-locus association studies; haplotype analyses(in which a number of variants, usually single-nucleotide polymorphisms occurring on the same gene, are analyzed as a unit) may be able to resolve these uncertainties. Investigating epistatic interactions between variants in other genes that might be involved in the same physiologic pathways would be an alternative means of deciphering the reason for discrepant genetic association results.A valid means of increasing the power (by reducing background noise)would be to stratify the patient sample according to clinically defined sub-types, such as obsession and compulsion subtypes, age at onset of the disorder, and severity of the disorder. Although many of the OCD genetics studies have incorporated investigations of these subtypes [65,66,68,77,84-86,89,107,118,132,133,145,148,149], the number of subjects decreases after stratification, thereby limiting the power of the studies. It may therefore be useful to employ other quantitative approaches in the design of the investigation: the possibility should be considered that OCD symptoms can be broken down into multiple dimensions that are continuous with the normal population [150]. This division would represent an important route to disentangling the complex inheritance of OCD. The results obtained from genetic investigations should be incorporated with clinical and epidemiologic parameters to elucidate correctly the cause of OCD. Future studies should also be extended to incorporate the screening of more polymorphisms, because high-resolution mapping within specific chromosomes will improve knowledge regarding the impact of genetic diversity within the genes or linked chromosomal regions in OCD. The advantages ofa gene-based over a single-nucleotide polymorphism based approach are becoming ever more apparent [151]. Therefore, a more complete assessment of candidate genes, possibly using haplotype blocks that span larger regions,is proposed. In addition, increasing the amount of information on human genome sequences and polymorphisms will make it possible to characterize the amount of sequence variation expressed in the brain and to delineate the potential effects that these variations may have on the development of OCD. Knowledge of new functional variants will emerge as researchers gain an understanding of the potential for genetic variants in the coding and regulatory regions to impact gene expression.

Catechol O-Methyltransferase↗

PubMed2004

Cis-acting regulatory variation in the human genome.

The systematic screening of the human genome for genetic variants that affect gene regulation should advance our fundamental understanding of phenotypic diversity and lead to the identification of alleles that modify disease risk. There are several challenges in localizing regulatory polymorphisms, including the wide spectrum of cis-acting regulatory mechanisms, the inconsistent effects of regulatory variants in different tissues, and the difficulty in isolating the causal variants that are in linkage disequilibrium with many other variants. We discuss the current state of knowledge and technologies used for mapping and characterizing genetic variation controlling human gene expression.

Alleles↗

PubMed2006

Vitamin D receptor genotypes/haplotypes and prostate cancer risk.

The vitamin D receptor (VDR) gene has been associated with prostate cancer, although previous results are somewhat equivocal. To further study this, we did a family-based case-control study (N = 918) of the association between prostate cancer and six common VDR variants: Cdx2, FokI, BsmI, ApaI, TaqI, and the poly-A microsatellite. Looking at each variant alone, only FokI and ApaI were associated with disease. The FokI FF genotype was inversely associated with prostate cancer among men with less advanced disease (i.e., Gleason score <7 and tumor stage <T2c), where the odds ratio OR was 0.56 [95% confidence interval (95% CI), 0.31-1.01; P = 0.05]. ApaI, carrying one or two copies of the A allele, exhibited a weak inverse association with disease (OR, 0.64; 95% CI, 0.39-1.03; P = 0.06); this association was strengthened in Caucasian men with more advanced disease (OR, 0.44; 95% CI, 0.21-0.93; P = 0.03). We observed inverse associations between disease and the four-locus FBAt haplotype (OR, 0.48; 95% CI, 0.30-0.76; P = 0.002) and the fbaT haplotype (OR, 0.60; 95% CI, 0.38-0.95; P = 0.03; i.e., in comparison with the FbaT haplotype). These were stronger among men with more advanced disease: for FBAt, the OR was 0.31 (95% CI, 0.16-0.61; P = 0.0008); for fbaT, the OR was 0.32 (95% CI, 0.16-0.64; P = 0.001). These observations support a role for VDR variants in prostate cancer risk but suggest that any potential causal variant(s) may reside on the haplotypes reported here. This would help explain the somewhat equivocal results for VDR genotype-level associations with prostate cancer.

Case-Control Studies↗

PubMed2025

Genome sequencing reveals the impact of pseudoexons in rare genetic disease.

PURPOSE: Advancements in sequencing technologies have significantly improved clinical genetic testing; yet, the diagnostic yield remains around 30% to 40%. Emerging technologies are now being deployed to address the remaining diagnostic gap. METHODS: We tested whether short-read genome sequencing could increase the diagnostic yield in individuals enrolled into the UCI-GREGoR research study, who had suspected Mendelian conditions and prior inconclusive testing. Two other collaborative research cohorts, focused on aortopathy and dilated cardiomyopathy, consisted of individuals who were undiagnosed but had not undergone harmonized prior testing. RESULTS: We sequenced 353 families (754 participants) and found a molecular diagnosis in 54 (15.3%) of them. Of these diagnoses, 55.5% were previously missed because the causative variants were in regions not originally interrogated. In 5 cases, they were deep intronic variants, all of which led to abnormal splicing and pseudoexons, as directly shown by RNA sequencing. All 5 of these variants had inconclusive spliceAI scores. In 26% of newly diagnosed cases, the causal variant could have been detected by exome sequencing reanalysis. CONCLUSION: Genome sequencing can overcome limitations of clinical genetic testing, such as the inability to call intronic variants. Our findings highlight pseudoexons as a common mechanism via which deep intronic variants cause Mendelian disease.

Humans↗

PubMed2004

Does haplotype diversity predict power for association mapping of disease susceptibility?

Many recent studies have established that haplotype diversity in a small region may not be greatly diminished when the number of markers is reduced to a smaller set of "haplotype-tagging" single-nucleotide polymorphisms (SNPs) that identify the most common haplotypes. These studies are motivated by the assumption that retention of haplotype diversity assures retention of power for mapping disease susceptibility by allelic association. Using two bodies of real data, three proposed measures of diversity, and regression-based methods for association mapping, we found no scenario for which this assumption was tenable. We compared the chi-square for composite likelihood and the maximum chi-square for single SNPs in diplotypes, excluding the marker designated as causal. All haplotype-tagging methods conserve haplotype diversity by selecting common SNPs. When the causal marker has a range of allele frequencies as in real data, chi-square decreases faster than under random selection as the haplotype-tagging set diminishes. Selecting SNPs by maximizing haplotype diversity is inefficient when their frequency is much different from the unknown frequency of the causal variant. Loss of power is minimized when the difference between minor allele frequencies of the causal SNP and a closely associated marker SNP is small, which is unlikely in ignorance of the frequency of the causal SNP unless dense markers are used. Therefore retention of haplotype diversity in simulations that do not mirror genomic allele frequencies has no relevance to power for association mapping. TagSNPs that are assigned to bins instead of haplotype blocks also lose power compared with random SNPs. This evidence favours a multi-stage design in which both models and density change adaptively.

Gene Frequency↗

PubMed2026

Multi-Ancestry Genome-Wide Association with Fine-Mapping Identifies Novel Loci for Pigment Dispersion Syndrome and Pigmentary Glaucoma.

PURPOSE: Pigment dispersion syndrome and pigmentary glaucoma are important causes of ocular hypertension and glaucomatous optic neuropathy, yet their genetic determinants remain incompletely defined, particularly across diverse ancestries. This study aimed to use a large multi-ancestry cohort from the All of Us Research Program to investigate the genetic basis of pigment dispersion syndrome and pigmentary glaucoma. DESIGN: Case-control study. PARTICIPANTS: In total, 572 cases and 37 808 controls with array genotyping and 537 cases and 35 493 controls with whole-genome sequencing. METHODS: Using electronic health record phenotyping in the All of Us Research Program, we performed multi-ancestry genome-wide association analyses using both array-based data and whole-genome sequencing-based data, comparing patients with pigment dispersion syndrome or pigmentary glaucoma to those without either condition. We also performed Firth penalized regression and Fisher analyses, and we performed principal component analyses to assess effect sizes across genetic ancestries. We applied statistical fine-mapping, examined for cross-trait overlap, and assessed expression quantitative trait locus associations for lead variants. MAIN OUTCOME MEASURES: P values and odds ratios of lead loci from genome-wide association analyses; size of credible sets determined from fine-mapping; allele frequency of lead variants in cases, controls, and the general population; expression quantitative trait loci effect size and P values linking lead variants to gene expression. RESULTS: We identified 4 loci reaching genome-wide significance across analyses, including signals near EPHA7 (which mediates cell-cell signaling), within TYR (involved in melanin synthesis and replicated from prior studies), within LINC01138, and near OTX2. Statistical fine-mapping refined 3 of these loci to single-variant 95% credible sets and narrowed the TYR locus to small credible sets, prioritizing possible causal variants. Effect estimates were broadly consistent across genetic ancestry clusters. Lead variants showed regulatory evidence in expression quantitative trait locus, including reduced EPHA7 expression. CONCLUSIONS: These findings implicate both melanogenesis and cell-cell adhesion and signaling pathways in pigment dispersion syndrome and pigmentary glaucoma. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Genome-wide association study↗

PubMed2006

Refined association mapping for a quantitative trait: weight in the H19-IGF2-INS-TH region.

Previous analyses have provided evidence for one or more loci affecting body weight in the H19-IGF2-INS-TH region on chromosome 11p15. To identify the location of a possible causal locus or loci we applied association analysis by composite likelihood to a large cohort under the Malecot model for body weight. A random sample of 2731 men in the UK were typed for eleven single nucleotide polymorphisms (SNPs) in IGF2, two SNPs in H19, one SNP in INS and one microsatellite marker in the TH genes. Using F tests appropriate to small marker sets, the superiority of regression over correlation was confirmed. All the evidence for association came from IGF2, with P= 0.007 for height-adjusted weight and P= 0.019 for weight additionally adjusted for smoking and alcohol drinking. Although the estimated point location for the suspected causal variant was close to IGF2 ApaI, the 95% confidence and support intervals covered most of IGF2 but none of the other loci. Identification of the causal SNP or SNPs within IGF2 will require typing of more variants in this region.

Body Mass Index↗

PubMed2005

BRAF polymorphisms and risk of melanocytic neoplasia.

Somatic mutations of the BRAF gene are common in melanomas and nevi but the contribution of polymorphisms in this gene to melanoma or nevus susceptibility remains unclear. An Australian melanoma case-control sample was typed for 16 single nucleotide polymorphisms (SNP) within the BRAF gene, and five SNP in three neighboring genes. The sample comprised 755 melanoma cases from 740 families stratified by family history of melanoma and controls from 635 unselected twin families (2,239 individuals). Ancestry of the cases and controls was recorded, and the twins had undergone skin examination to assess total body nevus count, degree of freckling, and pigmentation phenotype. Genotyping was carried out via primer extension followed by matrix-assisted laser desorption ionization-time of flight mass spectrometry. SNP in the BRAF gene were found to be weakly associated with melanoma status but not with development of nevi or freckles. The estimated proportion of attributable risk of melanoma due to variants in BRAF is 1.6%. This study shows that BRAF polymorphisms predispose to melanoma but the causal variant has yet to be determined. The burden of disease associated with this variant is greater than that associated with the major melanoma susceptibility locus CDKN2A, which has an estimated attributable risk of 0.2%.

Diseases in Twins↗