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Biomedical subjects

D Curtis

Publications and source records attributed to D Curtis.

At least 19 recordsLinked to original sources
PubMed2006

Fine mapping of a susceptibility locus for bipolar and genetically related unipolar affective disorders, to a region containing the C21ORF29 and TRPM2 genes on chromosome 21q22.3.

Linkage analyses of bipolar families have confirmed that there is a susceptibility locus near the telomere on chromosome 21q. To fine map this locus we carried out tests of allelic association using 30 genetic markers near the telomere at 21q22.3 in 600 bipolar research subjects and 450 ancestrally matched supernormal control subjects. We found significant allelic association with the microsatellite markers D21S171 (P=0.016) and two closely linked single-nucleotide polymorphisms, rs1556314 (P=0.008) and rs1785467 (P=0.025). A test of association with a three locus haplotype across the susceptibility region was significant with a permutation test of P=0.011. A two SNP haplotype was also significantly associated with bipolar disorder (P=0.01). Only two brain expressed genes, TRPM2 and C21ORF29 (TSPEAR), are present in the associated region. TRPM2 encodes a calcium channel receptor and TSPEAR encodes a peptide with repeats associated with epilepsy in the mouse. DNA from subjects who had inherited the associated marker alleles was sequenced. A base pair change (rs1556314) in exon 11 of TRPM2, which caused a change from an aspartic acid to a glutamic acid at peptide position 543 was found. This SNP showed the strongest association with bipolar disorder (P=0.008). Deletion of exon 11 of TRPM2 is known to cause dysregulation of cellular calcium homeostasis in response to oxidative stress. A second nonconservative change from arginine to cysteine at position 755 in TRPM2 (ss48297761) was also detected. A third nonconservative change from histidine to glutamic acid was found in exon 8 of TSPEAR. These changes need further investigation to establish any aetiological role in bipolar disorder.

Amino Acid Substitution↗
PubMed2006

Investigation of the ability of haplotype association and logistic regression to identify associated susceptibility loci.

While finely spaced markers are increasingly being used in case-control association studies in attempts to identify susceptibility loci, not enough is yet known as to the optimal spacing of such markers, their likely power to detect association, the relative merits of single marker versus multimarker analysis, or which methods of analysis may be optimal. Some investigations of these issues have used markers simulated under different theoretical models of population evolution. However the HapMap project and other sources provide real datasets which can be used to obtain a more realistic view of the performance of these approaches. SNPs around APOE and from two HapMap regions were used to obtain information regarding linkage disequilibrium (LD) relationships between polymorphisms, and these real patterns of LD were used to simulate datasets such as would be obtained in case-control studies were these SNPs to influence susceptibility to disease. The datasets obtained were analysed using tests for heterogeneity of estimated haplotype frequencies and using logistic regression analyses in which only main effects from each marker were considered. All markers surrounding the putative susceptibility locus were analysed, using sets of either 1, 2, 3 or 4 markers at a time. Some markers within 150 kb of the susceptibility locus were able to detect association. At distances less than 100 kb there was no correlation between the distance from the susceptibility locus and the strength of evidence for association. When the average inter-locus spacing is 25 kb many loci would not be detected, while when the spacing is as low as 2 kb one can be fairly confident that at least one marker will be in strong enough LD with the susceptibility locus to enable association to be detected, if the susceptibility locus has a strong enough effect relative to the sample size. With an inter-locus spacing of 4 kb some susceptibility loci did not have a marker locus in strong LD, potentially undermining the ability to detect association. There was little difference in the performance of haplotype-based analysis compared with logistic regression considering effects of each marker as separate. Multimarker analysis on occasion produced results which were much more highly significant than single marker analysis, but only very rarely. Our results support the view that if markers are randomly selected then a spacing as low as 2 kb is desirable. Multimarker analysis can sometimes be more powerful than single marker analysis so both should be performed. However, because it is rare for multimarker analysis to be much more highly significant than single marker analysis one should strongly suspect that when such results occur they may be due to mistakes in genotyping or through some other artefact. Haplotype analysis may be more prone to such problems than logistic regression, suggesting that the latter method might be preferred.

Apolipoproteins E↗
PubMed2006

Program report: GENECOUNTING support programs.

We describe a suite of programs which enhance the usability of GENECOUNTING, a program for estimating haplotype frequencies in unrelated subjects. The programs, called RUNGC, SCANASSOC, COMPGR, SCANGROUP and LDPAIRS, carry out likelihood ratio tests and permutation tests to detect differences in haplotype frequencies between cases and controls,or between predefined groups, and output likely haplotype assignments and tables of linkage disequilibrium statistics between all pairs of markers in a dataset.

Databases, Genetic↗
PubMed2004

Haplotype association analysis of discrete and continuous traits using mixture of regression models.

We present a regression-based method of haplotype association analysis for quantitative and dichotomous traits in samples consisting of unrelated individuals. The method takes account of uncertain phase by initially estimating haplotype frequencies and obtaining the posterior probabilities of all possible haplotype combinations in each individual, then using these as weights in a finite mixture of regression models. Using this method, different combinations of marker loci can be modeled, to find a parsimonious set of marker loci that are most predictive and therefore most likely to be closely associated with the a quantitative trait locus. The method has the additional advantage of being able to use individuals with some missing genotype data, by considering all possible genotypes at the missing markers. We have implemented this method using the SNPHAP and Mx programs and illustrated its use on published data on idiopathic generalized epilepsy.

Chromosome Mapping↗
PubMed2004

Further investigation of linkage disequilibrium SNPs and their ability to identify associated susceptibility loci.

There is currently considerable interest in the use of single-nucleotide polymorphisms (SNPs) to map disease susceptibility genes. The success of this method will depend on a number of factors including the strength of linkage disequilibrium (LD) between marker and disease loci. We used a data set of SNP genotypings in the region of the APOE disease susceptibility locus to investigate the likely usefulness of SNPs in case-control studies. Using the estimated haplotype structure surrounding and including the APOE locus, and assuming a codominant disease model, we treated each SNP in turn as if it were a disease susceptibility locus and obtained, for each disease locus and markers, the expected likelihood ratio test (LRT) to assess disease association. We were particularly interested in the power to detect association with the susceptibility polymorphism itself, the power of nearby markers to detect association, and the ability to distinguish between the susceptibility polymorphism and marker loci also showing association. We found that the expected LRT depended critically on disease allele frequencies. For disease loci with a reasonably common allele we were usually able to detect association. However, for only a subset of markers in the close neighbourhood of the disease locus was association detectable. In these cases we were usually, but not always, able to distinguish the disease locus from nearby associated marker loci. For some disease loci, no other loci demonstrated detectable association with the disease phenotype. We conclude that one may need to use very dense SNP maps in order to avoid overlooking polymorphisms affecting susceptibility to a common phenotype.

Alzheimer Disease↗
PubMed2004

Genome scan of Tourette syndrome in a single large pedigree shows some support for linkage to regions of chromosomes 5, 10 and 13.

OBJECTIVES: To localize genes influencing the susceptibility to Gilles de la Tourette syndrome (GTS) and associated chronic multiple tics (CMT). METHOD: A single, large, multiple affected pedigree containing 35 subjects diagnosed with GTS and a further 14 with CMT was genotyped for markers spanning the autosomes. Linkage analysis was carried out using classical lod score analysis and model-free lod score analysis. All markers were subjected to two-point analysis, and markers producing a two-point result significant at P<0.005 were subjected to three-point analysis using adjacent markers. RESULTS: The following markers produced at least one result significant at 0.005 using two-point analysis: D5S1981, D5S2050, D10S591, D10S189, D13S217, and D14S288. Three-point analysis with D5S2050 and D5S400 produced a lod of 2.9 with CMT. Three-point analysis of D10S591 and D10S189 produced lods of 1.9 with GTS and CMT. Three-point analysis of D13S217 and D13S171 produced a lod of 2.7 with GTS. No single haplotype appeared to account for the majority of cases within the pedigree. CONCLUSIONS: It seems likely that more than one susceptibility allele is present in the pedigree. Although none of the three positive regions is conclusively implicated, it seems probable that at least one contains a susceptibility locus. We recommend that association-based studies be carried out in these three regions to produce further evidence for a localization and to carry out fine-mapping.

Chromosome Mapping↗
PubMed2003

Assessing optimal neural network architecture for identifying disease-associated multi-marker genotypes using a permutation test, and application to calpain 10 polymorphisms associated with diabetes.

Biallelic markers, such as single nucleotide polymorphisms (SNPs), provide greater information for localising disease loci when treated as multilocus haplotypes, but often haplotypes are not immediately available from multilocus genotypes in case-control studies. An artificial neural network allows investigation of association between disease phenotype and tightly linked markers without requiring haplotype phase and without modelling any evolutionary history for the disease-related haplotypes. The network assesses whether marker haplotypes differ between cases and controls to the extent that classification of disease status based on multi-marker genotypes is achievable. The network is "trained" to "recognise" affection status based on supplied marker genotypes, and then for each multi-marker genotype it produces outputs which aim to approximate the associated affection status. Next, the genotypes are permuted relative to affection status to produce many random datasets and the process of training and recording of outputs is repeated. The extent to which the ability to predict affection for the real dataset exceeds that for the random datasets measures the statistical significance of the association between multi-marker genotype and affection. This permutation test performs well with simulated case-control datasets, particularly when major gene effects are present. We have explored the effects of systematically varying different network parameters in order to identify their optimal values. We have applied the permutation test to 4 SNPs of the calpain 10 (CAPN10) gene typed in a case-control sample of subjects with type 2 diabetes, impaired glucose tolerance, and controls. We show that the neural network produces more highly significant evidence for association than do single marker tests corrected for the number of markers genotyped. The use of a permutation test could potentially allow conditional analyses which could incorporate known risk factors alongside marker genotypes. Permuting only the marker genotypes relative to affection status and these risk factors would allow the contribution of the markers to disease risk to be independently assessed.

Calpain↗
PubMed2003

Variation in the DCP1 gene, encoding the angiotensin converting enzyme ACE, is not associated with increased susceptibility to Alzheimer's disease.

OBJECTIVES: To attempt to replicate previous reports that polymorphic variation in the DCP1 gene causes increased susceptibility to the development of Alzheimer's disease, either on its own or in interaction with the effects of the gene for apolipoprotein E (APOE). METHOD: Subjects older than 65 years of age consisting of 81 dementia patients diagnosed as having possible or probable Alzheimer's disease and 68 controls were obtained from Camden, Islington and Harlow psychiatric services. Subjects were genotyped for APOE alleles e2, e3 and e4, and the common insertion/deletion polymorphisms for DCP1* I/D were genotyped. RESULTS: There was no statistically significant difference in the frequency of the DCP1* insertion/deletion alleles between the cases and controls (X2 =0.04, 1 degree of freedom, not significant). When subjects were subdivided according to whether they possessed at least one copy of the APOE e4 allele, there were still no differences in DCP1 allele frequencies between cases and controls. CONCLUSIONS: Further research is needed to elucidate any role that the DCP1 polymorphism may play in relation to Alzheimer's disease. Previous studies may be false positive, or inconsistency in replication may be due to heterogeneity.

Aged↗
PubMed2003

Coeliac disease: investigation of proposed causal variants in the CTLA4 gene region.

Coeliac disease (CD) is an immune-mediated enteropathy triggered by gluten in genetically predisposed individuals. Patients with CD have an increased prevalence of other autoimmune disorders, including type 1 diabetes (T1D) and Graves' disease (GD). CD shares with these conditions certain HLA susceptibility alleles. A number of studies have also shown association of autoimmune diseases, including CD, with the CD28-cytotoxic T lymphocyte antigen 4 (CTLA4)-inducible costimulator (ICOS) region of chromosome 2q33, but until recently the precise causal variant has remained unknown. Recently, it was shown that, in GD, CT60 (+6230G>A), a single nucleotide polymorphism (SNP) at the end of the CTLA4 transcript, is associated with an alteration in the ratio of splice forms of the CTLA4 gene and that this ratio affects disease susceptibility. A similar but weaker association was found with T1D. There is also an independent association of GD and T1D with the SNP MH30 (-23 327G>C), which possibly affects promoter region function. Hypothesizing that CT60 and MH30 may be causal variants in other autoimmune disorders, we investigated these SNPs in CD using 149 family trios and 100 unrelated/unaffected controls. No association was detected with either SNP using both the transmission disequilibrium test (TDT) and case-control methods. Our study appears to have good power to detect moderate genetic effects, but possibly these SNPs exert too weak an effect on risk of CD to have been detected in our sample. Alternatively, the previously noted association of CD with the CTLA4 gene region may be due to different causal variants. Unlike T1D and GD, CD is not a true autoimmune disease, and CD has different associations at the CTLA4 exon 1 SNP +49G>A from all other autoimmune disorders. MH30, CT60, and other SNPs in the region may still warrant further investigation in other CD samples.

Antigens, CD↗
PubMed2002

Extension of conditional model-free likelihood-based linkage analysis to additive and other models.

We have previously described extending our method of 'model-free' linkage analysis, implemented in the MFLINK program, in order to deal with liability classes. This allows a new form of conditional two-locus linkage analysis, meaning that the genotypes of a known risk locus can be used to define liability classes so that their effects can be incorporated in tests for linkage at additional loci. In this method, relationships between transmission models for different liability classes were constrained so that there was a constant multiplicative effect on penetrance values. Here we present further extensions to the method to allow for different relationships. In particular, rather than only having a multiplicative effect on risk of affection we now allow specification of a multiplicative effect on risk of non-affection, or a combination of both relationships, across liability classes. We now also allow specification of an additive effect on penetrance. By way of example, we apply these methods to genome scan data for Alzheimer's disease using apolipoprotein E genotype to define liability classes. We show that, although in general the different methods produce results which tend to be quite highly correlated, certain markers can produce quite different results according to the method applied and that these could well lead to differences of interpretation. Without knowing a priori which relationship is likely to be most appropriate to describe the overall combined effect of the two loci one might be obliged to apply a number of different methods. This in turn may lead to the familiar difficulties associated with multiple testing. Nevertheless, the new method allows researchers greater flexibility in analysing linkage data for diseases in which one or more risk polymorphisms have already been identified.

Genetic Linkage↗
PubMed2002

A quick and simple method for detecting subjects with abnormal genetic background in case-control samples.

It is important that case-control samples be drawn from a genetically homogeneous population in order to avoid artefactual false positive results and to enhance power to detect disease mutations and markers in linkage disequilibrium with them. Tests which simply compare overall marker allele frequencies between cases and controls will fail to identify a relatively small number of subjects drawn from a different genetic background who could usefully be discarded from the sample. Such subjects can be identified using multilocus tests, but previously described tests have been unnecessarily complex and cumbersome for this simple application. We describe a straightforward test, implemented in the CHECKHET program, which uses a measure of genetic difference and permutation procedures to rapidly identify such subjects using genotypes from multiple unlinked markers. It seems to perform reasonably well on simulated data, and with real data appears to identify two abnormal subjects within a case-control sample. We recommend that such tests be routinely applied to case-control samples once sufficient numbers of markers have been genotyped within them.

Case-Control Studies↗
PubMed2002

Analysis of candidate genes on chromosome 19 in coeliac disease: an association study of the KIR and LILR gene clusters.

Coeliac disease is strongly heritable, with more than half of the genetic susceptibility estimated to come from genes outside the HLA region. Several candidate regions have been suggested from genome-wide linkage studies including chromosome 19q13.4 where linkage has been replicated between populations. The natural killer (NK) cell immunoglobulin-like receptors (KIRs) and leukocyte immunoglobulin-like receptor (LILR, also known as ILT and LIR) gene clusters lie within this region in the leukocyte receptor cluster (LRC). KIR molecules are involved in cytotoxic lymphocyte function and expressed by intraepithelial T and NK cells in the duodenum. We studied 132 unrelated UK Caucasian coeliac patients and their parents together with a control group of 171 UK Caucasians. PCR-SSP for KIR2DL1, KIR2DL2, KIR2DL3, KIR2DL5, LILRA3 (ILT6), LILRA3 deletion and an LILRA3 exon 3 single nucleotide polymorphism (SNP) allowed classification of KIR genotypes into five categories and determination of homozygosity or heterozygosity for the common A and B type KIR haplotypes (as defined in the text) and for the LILRA3 deletion. Case-control analysis found no association of the five KIR genotype categories, the A or B KIR haplotypes, the LILRA3 gene deletion or the LILRA3 exon 3 SNP with coeliac disease. A transmission disequilibrium test also found no association of the A and B KIR haplotypes or the LILRA3 gene deletion with coeliac disease.

Case-Control Studies↗
PubMed2001

The views of Otago urban and rural general practitioners on mental health services.

AIM: To examine the views of Otago general practitioners (GPs) about local mental health services and their role in providing such health care. METHODS: A questionnaire was distributed to all GPs working in Otago. RESULTS: 100 replies (59%) were received. There were large differences between GPs in the estimated numbers of patients with psychiatric conditions they were seeing. 85% were keen on sharing management of patients with mental health services. Average confidence levels for diagnosis and management of depression and anxiety were good. GPs felt less confident about psychosis, somatisation, eating and personality disorders. Obstacles to GPs doing more mental health work included time, cost, access to specialist services and training. On balance, GPs viewed the present mental health services as adequate. CONCLUSIONS: GPs appeared prepared to do more mental health work if the barriers of cost and time could be overcome and they were provided with adequate education and backup from specialised services.

Attitude of Health Personnel↗