Biomedical subjects

Chris Wallace

Publications and source records attributed to Chris Wallace.

13 recordsLinked to original sources

PubMed2025

Exploiting pleiotropy to enhance variant discovery with functional false discovery rates.

The cost of recruiting participants for genome-wide association studies (GWASs) can limit sample sizes and hinder the discovery of genetic variants. Here we introduce the surrogate functional false discovery rate (sfFDR) framework that integrates summary statistics of related traits to increase power. The sfFDR framework provides estimates of FDR quantities such as the functional local FDR and q value, and uses these estimates to derive a functional P value for type I error rate control and a functional local Bayes' factor for post-GWAS analyses. Compared with a standard analysis, sfFDR substantially increased power (equivalent to a 52% increase in sample size) in a study of obesity-related traits from the UK Biobank and discovered eight additional lead SNPs near genes linked to immune-related responses in a rare disease GWAS of eosinophilic granulomatosis with polyangiitis. Collectively, these results highlight the utility of exploiting related traits in both small and large studies.

Humans↗

PubMed2025

MDA5 variants trade antiviral activity for protection from autoimmune disease.

Loss-of-function variants in MDA5, a key sensor of double-stranded RNA from viruses and retroelements, have been associated with protection from type 1 diabetes (T1D) in genome-wide association studies (GWAS). MDA5 loss-of-function variants have also been reported to increase the risk of inflammatory bowel disease (IBD). Whether these associations are linked or extend to other diseases remains unclear. Here, fine-mapping analysis of four large GWAS datasets shows that T1D-protective loss-of-function MDA5 variants also protect against psoriasis and hypothyroidism, while increasing the risk of IBD. The degree of autoimmune protection and IBD risk were linearly proportional. The magnitudes of the odds ratios for autoimmune protection and IBD risk were larger for rare MDA5 variants than for common variants, which were differentially expressed in different geographic populations. Our analysis suggests MDA5 genetic variants offer a direct fitness trade-off between viral clearance and autoimmune tissue damage.

Interferon-Induced Helicase, IFIH1↗

PubMed2025

Penalised regression improves imputation of cell-type specific expression using RNA-seq data from mixed cell populations compared to domain-specific methods.

Gene expression studies often use bulk RNA sequencing of mixed cell populations because single cell or sorted cell sequencing may be prohibitively expensive. However, mixed cell studies may miss expression patterns that are restricted to specific cell populations. Computational deconvolution can be used to estimate cell fractions from bulk expression data and infer average cell-type expression in a set of samples (e.g., cases or controls), but imputing sample-level cell-type expression is required for more detailed analyses, such as relating expression to quantitative traits, and is less commonly addressed. Here, we assessed the accuracy of imputing sample-level cell-type expression using a real dataset where mixed peripheral blood mononuclear cells (PBMC) and sorted (CD4, CD8, CD14, CD19) RNA sequencing data were generated from the same subjects (N=158), and pseudobulk datasets synthesised from eQTLgen single cell RNA-seq data. We compared three domain-specific methods, CIBERSORTx, bMIND and debCAM/swCAM, and two cross-domain machine learning methods, multiple response LASSO and ridge, that had not been used for this task before. We also assessed the methods according to their ability to recover differential gene expression (DGE) results. LASSO/ridge showed higher sensitivity but lower specificity for recovering DGE signals seen in observed data compared to deconvolution methods, although LASSO/ridge had higher area under curves than deconvolution methods. Machine learning methods have the potential to outperform domain-specific methods when suitable training data are available.

Humans↗

PubMed2006

Linkage analysis using co-phenotypes in the BRIGHT study reveals novel potential susceptibility loci for hypertension.

Identification of the genetic influences on human essential hypertension and other complex diseases has proved difficult, partly because of genetic heterogeneity. In many complex-trait resources, additional phenotypic data have been collected, allowing comorbid intermediary phenotypes to be used to characterize more genetically homogeneous subsets. The traditional approach to analyzing covariate-defined subsets has typically depended on researchers' previous expectations for definition of a comorbid subset and leads to smaller data sets, with a concomitant attrition in power. An alternative is to test for dependence between genetic sharing and covariates across the entire data set. This approach offers the advantage of exploiting the full data set and could be widely applied to complex-trait genome scans. However, existing maximum-likelihood methods can be prohibitively computationally expensive, especially since permutation is often required to determine significance. We developed a less computationally intensive score test and applied it to biometric and biochemical covariate data, from 2,044 sibling pairs with severe hypertension, collected by the British Genetics of Hypertension (BRIGHT) study. We found genomewide-significant evidence for linkage with hypertension and several related covariates. The strongest signals were with leaner-body-mass measures on chromosome 20q (maximum LOD = 4.24) and with parameters of renal function on chromosome 5p (maximum LOD = 3.71). After correction for the multiple traits and genetic locations studied, our global genomewide P value was .046. This is the first identity-by-descent regression analysis of hypertension to our knowledge, and it demonstrates the value of this approach for the incorporation of additional phenotypic information in genetic studies of complex traits.

Chromosome Mapping↗

PubMed2006

Increased support for linkage of a novel locus on chromosome 5q13 for essential hypertension in the British Genetics of Hypertension Study.

Human hypertension arises from a combination of genetic factors and lifestyle influences. With cardiovascular disease set to become the number 1 cause of death worldwide, it is important to understand the etiologic mechanisms for hypertension, because these might provide new routes to improved treatment. The British Genetics of Hypertension Study has recently published a primary genome screen that identified 4 chromosomal regions of interest. We have now genotyped additional markers to confirm the most promising regions for follow-up studies. Thirty-four additional microsatellites were genotyped in our severely hypertensive affected sibling pair resource (now 1635 families with 2142 affected sibling pairs), leading to a substantial increase in information content in the regions of interest. We found increased support for linkage of chromosome 5q13 to human hypertension (multipoint logarithm of odds=2.50) with 3 adjacent markers yielding single point logarithm of odds scores of 3.22, 2.84, and 2.51. The placement of additional markers on 2q, 6q, and 9q diminished support for linkage in these regions. However, the addition of new data and families identified novel regions of interest on chromosomes 1q and 11q. The 3 positive markers in the chromosome 5 region were also genotyped in 712 distinct parent-offspring trios with the same severe phenotype to replicate linkage and association. Borderline support for replication was found (P=0.07). We found increased evidence for linkage and borderline-significant evidence for association for a hypertension susceptibility locus on chromosome 5q13 that is worthy of detailed fine mapping and assessment of candidate genes.

Chromosome Mapping↗

PubMed2006

Two-dimensional genome-scan identifies novel epistatic loci for essential hypertension.

It is well established that gene interactions influence common human diseases, but to date linkage studies have been constrained to searching for single genes across the genome. We applied a novel approach to uncover significant gene-gene interactions in a systematic two-dimensional (2D) genome-scan of essential hypertension. The study cohort comprised 2076 affected sib-pairs and 66 affected half-sib-pairs of the British Genetics of HyperTension study. Extensive simulations were used to establish significance thresholds in the context of 2D genome-scans. Our analyses found significant and suggestive evidence for loci on chromosomes 5, 9, 11, 15, 16 and 19, which influence hypertension when gene-gene interactions are taken into account (5q13.1 and 11q22.1, two-locus lod score=5.72; 5q13.1 and 19q12, two-locus lod score=5.35; 9q22.3 and 15q12, two-locus lod score=4.80; 16p12.3 and 16q23.1, two-locus lod score=4.50). For each significant and suggestive pairwise interaction, the two-locus genetic model that best fitted the data was determined. Regions that were not detected using single-locus linkage analysis were identified in the 2D scan as contributing significant epistatic effects. This approach has discovered novel loci for hypertension and offers a unique potential to use existing data to uncover novel regions involved in complex human diseases.

Computational Biology↗

PubMed2006

Improved power offered by a score test for linkage disequilibrium mapping of quantitative-trait loci by selective genotyping.

Selective genotyping is used to increase efficiency in genetic association studies of quantitative traits by genotyping only those individuals who deviate from the population mean. However, selection distorts the conditional distribution of the trait given genotype, and such data sets are usually analyzed using case-control methods, quantitative analysis within selected groups, or a combination of both. We show that Hotelling's T(2) test, recently proposed for association studies of one or several tagging single-nucleotide polymorphisms in a prospective (i.e., trait given genotype) design, can also be applied to the retrospective (i.e., genotype given trait) selective-genotyping design, and we use simulation to demonstrate its improved power over existing methods.

Data Interpretation, Statistical↗

PubMed2006

Chromosome 2p shows significant linkage to antihypertensive response in the British Genetics of Hypertension Study.

There is a lack of consistently linked loci influencing blood pressure and hypertension status, and this may be because of genetic or phenotypic heterogeneity. We hypothesize that stratification of subjects by response to antihypertensive drug groups could be used to stringently define subsets that will have reduced genetic and etiologic heterogeneity, by partitioning contrasting mechanisms of hypertension and, thus, enhancing gene finding. We investigated the British Genetics of Hypertension Study population, which is composed of 2142 severely hypertensive white affected sibling pairs. Nonresponse to antihypertensive therapy was defined as an on-treatment blood pressure of >140/90 mm Hg or a difference between prediagnosis and on-treatment blood pressure of <20 mm Hg. Of the nonresponders, there were 89 sibling pairs (AB) who were both on antihypertensive therapy that inhibit the renin-angiotensin system (angiotensin-converting enzyme inhibitors, angiotensin II type-1 receptor blockers, or beta-blockers), and 76 sibling pairs (CD) who were both on drugs that do not (calcium channel blockers or diuretics). Nonparametric linkage analysis carried out using markers from a 10-cM genome scan and additional "grid tightening" markers showed significant linkage in the AB group on chromosome 2p (logarithm of odds=4.84 at 90.68 Kosambi cM) and suggestive linkage for the CD group on chromosome 10q (logarithm of odds=2.83 at 125.96 Kosambi cM). The AB linkage locus attained genomewide significance after simulation using 10,000 replicates (P=0.005). This locus may contain a gene for the salt-sensitive form of hypertension and/or a pharmacogenetic locus affecting drug response. We have demonstrated for the first time identification of a significant locus by partitioning different pathways of hypertension using drug response.

Adrenergic beta-Antagonists↗

PubMed2006

Haplotypes of the beta-2 adrenergic receptor associate with high diastolic blood pressure in the Caerphilly prospective study.

OBJECTIVES: Current evidence demonstrates that both genetic and environmental factors influence blood pressure. The sympathetic nervous system is a key player in blood pressure control and functional genetic variants of the beta-2 adrenergic receptor (B2AR) have been identified and implicated in the pathogenesis of hypertension. The present study aimed to determine the effects of common haplotypes of the B2AR gene upon blood pressure in the Caerphilly Prospective Study. DESIGN: Two thousand five hundred and twelve men (aged 45-59 years) participated in the study. We selected individuals in the upper (n = 347) and lower (n = 279) quintiles of the diastolic blood pressure distribution fixed at two time points [phase 2 (1984-88) or phase 3 (1989-93)] as cases and controls. METHODS: We analysed two functional polymorphisms (Arg16Gly and Gln27Glu) of B2AR and their haplotypes. RESULTS: We found a higher risk of hypertension in individuals homozygous for the Gln27 compared to those individuals homozygous for Glu27 [odds ratio (OR) = 1.94; 95% confidence interval (CI) = 1.34-2.81; P = 0.001]. Three haplotypes (Gly16Gln27, Gly16Glu27 and Arg16Gln27) were present in both quintile groups. Logistic regression analysis showed that haplotypes with a Gln27 allele (Gly16Gln27 and Arg16Gln27) conferred a significantly higher risk for hypertension than the Gly16Glu27 haplotype (OR = 1.55; 95% CI = 1.11-2.17, OR = 1.37; 95% CI = 1.04-1.81; P = 0.009 and P = 0.027, respectively). However, there was no evidence to support a statistically significant difference in odds ratios for the Gly16Gln27 and Arg16Gln27 haplotypes (P = 0.477), suggesting that it is the Gln27 allele alone, rather than any haplotype, which best explains the association. CONCLUSIONS: In a prospectively studied Caucasian male cohort, high diastolic blood pressure was associated with B2AR haplotypes containing the pro-downregulatory Gln27 variant.

Blood Pressure↗

PubMed2005

Haplotypes of the WNK1 gene associate with blood pressure variation in a severely hypertensive population from the British Genetics of Hypertension study.

Mutations in the WNK1 gene cause Gordon's syndrome, a rare Mendelian form of hypertension. We assessed whether common WNK1 variants might also contribute to essential hypertension (EH), a multifactorial disorder affecting > 25% of the adult population worldwide. A panel of 19 single nucleotide polymorphisms (SNPs) spanning the gene was selected from public databases and was genotyped in 100 white European families to determine the pattern of linkage disequilibrium, haplotype structure and tagging SNPs for the WNK1 locus. Eight tagging SNPs were identified with 90% power to predict common WNK1 haplotypes and SNPs. Family-based association tests were used to test for association with EH and severity of hypertension in 712 severely hypertensive families from the MRC British Genetics of Hypertension study resource. No association was found between WNK1 polymorphisms or haplotypes with hypertension; however, one SNP rs1468326, located 3 kb from the WNK1 promoter, was found to be nominally associated with severity of hypertension, with both systolic blood pressure (BP) (Z = +2.24, P = 0.025) and diastolic BP (Z = +1.99, P = 0.046). We also found nominal support for association of one common WNK1 haplotype with increased systolic BP (Z = +1.91, P = 0.053). This is the first study to perform haplotype association analysis of the WNK1 gene with EH. This finding of association between a SNP near the promoter region and the severity of hypertension suggests that increased expression of WNK1 might contribute to BP variability and susceptibility to EH similar to the mechanism of hypertension observed in Gordon's syndrome.

Adult↗

PubMed2003

Estimating the relative recurrence risk ratio using a global cross-ratio model.

The relative recurrence risk ratio lambdaR (and particularly the sibling recurrence risk ratio, lambdaS) is often of interest to those wanting to quantify the genetic contribution towards risk of disease or to discriminate between different genetic models. However, estimating lambdaR for complex diseases for which genetic and environmental risk factors are both involved is not straightforward. Ignoring environmental factors may lead to inflated estimates of lambdaR. We present a marginal model which uses a copula function to model the association in cumulative incidence rates between pairs of relatives. This model is applicable to present-state data and allows estimation of risk of disease in a pair of relatives (and hence lambdaR), given measured environmental covariates. We apply the model to leprosy among sibling pairs from the Karonga district, Malawi. If risk factors are ignored, the apparent lambdaS in this population is over 3. Accounting for known nongenetic risk factors reduces it to just under 2.

Algorithms↗

PubMed2003

Trends in drug overdose deaths in England and Wales 1993-98: methadone does not kill more people than heroin.

AIMS: To test the hypothesis that methadone is responsible for a greater increase in overdose deaths than heroin, and causes proportionally more overdose deaths than heroin at weekends. DESIGN AND SETTING: Multivariate analysis of 3961 death certificates mentioning heroin, morphine and/or methadone held on the Office for National Statistics drug-related poisoning mortality database from 1993 to 1998 in England and Wales. MEASUREMENTS: Percentage increase in deaths by year by drug, odds ratio (OR) of dying at the weekend from methadone-related overdose compared to dying from heroin/morphine overdose. FINDINGS: From 1993 to 1998, annual opiate overdose deaths increased from 378 to 909. There was a 24.7% (95% confidence interval (CI) 22-28%) yearly increase in heroin deaths compared to 9.4% (95% CI 6-13%) for methadone only. This difference was significant (P < 0.001 by test of interaction) after adjustment for sex, age group, polydrug use, area of residence and underlying cause of death. The largest number of deaths occurred on Saturday (673). The OR of death from methadone overdose on Saturday and Sunday was 1.48 (95% CI 1.29-1.71) for methadone-only deaths compared to dying from heroin/morphine at the weekend after adjustment for other covariates, but the OR was not significant (1.09, 95% CI 0.95-1.25) if the weekend was defined as Friday and Saturday. CONCLUSIONS: There was no evidence that the threefold increase in deaths over time was due to methadone. There was equivocal support only for the hypothesis that there was an excess of deaths from methadone at weekends. Increased interventions to prevent overdose among injectors in England and Wales are long overdue.

Adolescent↗

PubMed2003

Estimating the relative recurrence risk ratio for leprosy in Karonga District, Malawi.

Leprosy is a chronic disease caused by infection with Mycobacterium leprae. Susceptibility to leprosy is influenced by both genetic and non-genetic factors and the disease is known to cluster in families. One measure of genetic effect is the relative recurrence risk ratio, lambdaR. Estimates of this parameter can be inflated if environmental risk factors which also cluster in families, such as household contact, are not properly accounted for. We present the results of fitting a cross ratio model that allows estimation of the odds ratio of disease conditional on disease or no disease in a given relative, given measured covariates. From this model we can predict fitted values for lambdaR that represent the familial risk not accounted for by other covariates including observed household contact. If all covariates could be measured, this would be the 'genetic relative risk ratio'. We find lambdaR > 1 for all relative pairs except grandparent-grandchild, and lambdaR > 2 for siblings. Though not in itself evidence for a strong genetic susceptibility to leprosy, this result is consistent with much other evidence which suggests susceptibility to leprosy is under the control of many factors, the strongest of which may be non-genetic, with host genetics playing a small but significant role.

Adolescent↗