Biomedical subjects

P Holmans

Publications and source records attributed to P Holmans.

At least 19 recordsLinked to original sources

PubMed2005

Genome wide significant linkage in schizophrenia conditioning on occurrence of depressive episodes.

BACKGROUND: Schizophrenia shows substantial clinical heterogeneity. One common important clinical variable in presentation is the occurrence of episodes of major depression. METHODS: We undertook analyses in an attempt to detect loci that influence susceptibility to, or modify the clinical expression of, schizophrenia according to the occurrence of episodes of major depression. We used a logistic regression framework in which lifetime presence/absence of major depression was entered as a covariate in the linkage analysis of our UK schizophrenia affected sibling pair series (168 affected sibling pairs typed for a 10 cM map of microsatellite markers). RESULTS: Inclusion of presence/absence of depression as a covariate detected a genome wide significant linkage signal on chromosome 4q28.3 at 130.7 cM (LOD = 4.59; p = 0.038; increase in maximum LOD over univariate analysis (ILOD) = 3.62). Inclusion of the depression covariate also showed suggestive evidence of linkage on 20q11.21 (LOD = 4.10; expected to occur by chance 0.093 times per genome scan, ILOD = 2.83). CONCLUSIONS: Our findings identify loci that may harbour genes that play a role in susceptibility to, or modify the risk of, episodes of major depression in people with schizophrenia.

Analysis of Variance↗

PubMed2005

Effect of genotyping error on type-I error rate of affected sib pair studies with genotyped parents.

OBJECTIVE: In affected sib pair studies without genotyped parents the effect of genotyping error is generally to reduce the type I error rate and power of tests for linkage. The effect of genotyping error when parents have been genotyped is unknown. We investigated the type I error rate of the single-point Mean test for studies in which genotypes of both parents are available. METHODS: Datasets were simulated assuming no linkage and one of five models for genotyping error. In each dataset, Mendelian-inconsistent families were either excluded or regenotyped, and then the Mean test applied. RESULTS: We found that genotyping errors lead to an inflated type I error rate when inconsistent families are excluded. Depending on the genotyping-error model assumed, regenotyping inconsistent families has one of several effects. It may produce the same type I error rate as if inconsistent families are excluded; it may reduce the type I error, but still leave an anti-conservative test; or it may give a conservative test. Departures of the type I error rate from its nominal level increase with both the genotyping error rate and sample size. CONCLUSION: We recommend that markers with high error rates either be excluded from the analysis or be regenotyped in all families.

Family↗

PubMed2005

Stage 2 of the Wellcome Trust UK-Irish bipolar affective disorder sibling-pair genome screen: evidence for linkage on chromosomes 6q16-q21, 4q12-q21, 9p21, 10p14-p12 and 18q22.

Bipolar affective disorder (BPAD) is a common psychiatric disorder with complex genetic aetiology. We have undertaken a genome-wide scan in one of the largest samples of bipolar affected sibling pairs (ASPs) using a two-stage approach combining sample splitting and marker grid tightening. In this second stage analysis, we have examined 17 regions that achieved a nominally significant maximum likelihood LOD score (MLS) threshold of 0.74 (or 1.18 for the X-chromosome) in stage one. The second stage has added 135 ASP families to bring the total stage 2 sample to 395 ASPs. In total, 494 microsatellite markers have been used to screen the human genome at a density of 10 cM in the first stage sample (260 ASPs) and 5 cM in the second stage. Under the broad diagnostic model, two markers gave LOD scores exceeding 3 with two-point analysis: D4S392 (LOD=3.30) and D10S197 (LOD=3.18). Multipoint analysis demonstrated suggestive evidence of linkage between BPAD and chromosomal regions 6q16-q21 (MLS=2.61) and 4q12-q21 (MLS=2.38). 6q16-q21 is of particular interest because our data, together with those from two recent genome scans, make this the best supported linkage region in BPAD. Further, our data show evidence of a gender effect at this locus with increased sharing predominantly within the male-male pairs. Our scan also provides support for linkage (MLS> or =1.5) at several other regions that have been implicated in meta-analyses of bipolar disorder and/or schizophrenia including 9p21, 10p14-p12 and 18q22.

Bipolar Disorder↗

PubMed2005

Design of case-controls studies with unscreened controls.

Traditionally in genetic case-control studies controls have been screened to exclude subjects with a personal history of illness. This control group has the advantage of optimal power to detect loci involved in illness, but requires more work and may incur substantial cost in recruitment. An alternative approach to screening is to use unscreened controls sampled from the general population. Such controls are generally plentiful and inexpensive, but in general there is a risk that some may have the same disease as the cases, which will reduce power to detect associations. We have quantified the extent of this power loss, and produced mathematical formulae for the number of unscreened controls necessary to achieve the same power as a fixed sample of screened controls. The effect of using unscreened controls will also depend on the ratio of the number of screened controls to cases specified in the original study design, and this is also investigated. We have also investigated the cost-benefits of the screened and unscreened approaches, according to variation in the relative costs of sampling screened and unscreened controls, together with genotyping costs. We have, thus, identified the range of situations in which using unscreened controls is a cost-effective alternative to the screened control method and could be considered when designing a study. In many of the typical, real-world situations in complex genetics, the use of unscreened controls is potentially cost-effective and can, in general, be considered for disorders with population prevalence Kp < 0.2. With the steady reduction in genotyping costs and the availability of common sets of "population controls" this design is likely to become increasingly cost effective.

Alleles↗

PubMed2004

Bayesian trio models for association in the presence of genotyping errors.

Errors in genotyping can greatly affect family-based association studies. If a mendelian inconsistency is detected, the family is usually removed from the analysis. This reduces power, and may introduce bias. In addition, a large proportion of genotyping errors remain undetected, and these also reduce power. We present a Bayesian framework for performing association studies with SNP data on samples of trios consisting of parents with an affected offspring, while allowing for the presence of both detectable and undetectable genotyping errors. This framework also allows for the inclusion of missing genotypes. Associations between the SNP and disease were modelled in terms of the genotypic relative risks. The performances of the analysis methods were investigated under a variety of models for disease association and genotype error, looking at both power to detect association and precision of genotypic relative risk estimates. As expected, power to detect association decreased as genotyping error probability increased. Importantly, however, analyses allowing for genotyping error had similar power to standard analyses when applied to data without genotyping error. Furthermore, allowing for genotyping error yielded relative risk estimates that were approximately unbiased, together with 95% credible intervals giving approximately correct coverage. The methods were also applied to a real dataset: a sample of schizophrenia cases and their parents genotyped at SNPs in the dysbindin gene. The analysis methods presented here require no prior information on the genotyping error probabilities, and may be fitted in WinBUGS.

Alleles↗

PubMed2003

A systematic genomewide linkage study in 353 sib pairs with schizophrenia.

We undertook a genomewide linkage study in a total of 353 affected sib pairs (ASPs) with schizophrenia. Our sample consisted of 179 ASPs from the United Kingdom, 134 from Sweden, and 40 from the United States. We typed 372 microsatellite markers at approximately 10-cM intervals. Our strongest finding was a LOD score of 3.87 on chromosome 10q25.3-q26.3, with positive results being contributed by all three samples and a LOD-1 interval of 15 cM. This finding achieved genomewide significance (P<.05), on the basis of simulation studies. We also found two regions, 17p11.2-q25.1 (maximum LOD score [MLS] = 3.35) and 22q11 (MLS = 2.29), in which the evidence for linkage was highly suggestive. Linkage to all of these regions has been supported by other studies. Moreover, we found strong evidence for linkage (genomewide P<.02) to 17p11.2-q25.1 in a single pedigree with schizophrenia. In our view, the evidence is now sufficiently compelling to undertake detailed mapping studies of these three regions.

Genetic Linkage↗

PubMed2003

Updated results of the United Kingdom linkage-based genome screen in multiple sclerosis.

In 1996, we reported the results of a linkage genome screen based on 129 UK multiple sclerosis multiplex families, together with follow-up typing of interesting regions in a second set of families. We have now completed screening the remainder of the genome in this second set of United Kingdom families by typing 242 microsatellite markers. These data have been analysed together with those previously published, resulting in the largest currently available whole genome linkage dataset from a single population in multiple sclerosis. Four new regions of potential linkage (chromosomes 10p, 11p, 19p, 20p) not previously described were identified. In the combined analysis of all 226 families, a total of five regions of suggestive linkage are seen (chromosomes 1p, 6p, 14q, 17q, Xq), where only one would have been expected to occur by chance alone.

Alleles↗

PubMed2003

Genome-wide scan of bipolar disorder in 65 pedigrees: supportive evidence for linkage at 8q24, 18q22, 4q32, 2p12, and 13q12.

The purpose of this study was to assess 65 pedigrees ascertained through a Bipolar I (BPI) proband for evidence of linkage, using nonparametric methods in a genome-wide scan and for possible parent of origin effect using several analytical methods. We identified 15 loci with nominally significant evidence for increased allele sharing among affected relative pairs. Eight of these regions, at 8q24, 18q22, 4q32, 13q12, 4q35, 10q26, 2p12, and 12q24, directly overlap with previously reported evidence of linkage to bipolar disorder. Five regions at 20p13, 2p22, 14q23, 9p13, and 1q41 are within several Mb of previously reported regions. We report our findings in rank order and the top five markers had an NPL>2.5. The peak finding in these regions were D8S256 at 8q24, NPL 3.13; D18S878 at 18q22, NPL 2.90; D4S1629 at 4q32, NPL 2.80; D2S99 at 2p12, NPL 2.54; and D13S1493 at 13q12, NPL 2.53. No locus produced statistically significant evidence for linkage at the genome-wide level. The parent of origin effect was studied and consistent with our previous findings, evidence for a locus on 18q22 was predominantly from families wherein the father or paternal lineage was affected. There was evidence consistent with paternal imprinting at the loci on 13q12 and 1q41.

Adolescent↗

PubMed2003

Allowing for genotyping error in analysis of unmatched case-control studies.

A commonly-used method for testing for association between disease and a single-nucleotide polymorphism (SNP) is to compare the frequencies of the SNP genotypes in a sample of unrelated cases to those in a sample of unrelated controls drawn from the same population (an unmatched case-control study). A drawback of such a study is that it is impossible to detect genotyping errors, and few methods have been developed to allow for the presence of undetected genotyping errors. In this paper, we obtain analytic formulae for estimates of genotypic relative risks in terms of error probability (e). In general, e will be unknown. We investigate the effect of assuming both correct and incorrect values of e on power and type I error, and also on the genotypic relative risk estimates. The choice of e was found to have no effect on power or Type I error probability (provided a 2df test was used, allowing relative risks of homozygotes and heterozygotes to differ). However, overestimating e in the presence of a true association was found in general to bias relative risk estimates away from the null, with underestimates of e having the opposite effect. Although e is unknown, it may be estimated from an external "validation" study, such as genotyping a sample of unrelated individuals twice and counting the discrepancies. Simulation results suggest that, for such a study, 25 individuals would be sufficient to give approximately unbiased estimates of relative risks.

Case-Control Studies↗

PubMed2002

A genome-wide screen for linkage in Nordic sib-pairs with multiple sclerosis.

Genetic factors influence susceptibility to multiple sclerosis but the responsible genes remain largely undefined, association with MHC class II alleles being the only established genetic feature of the disease. The Nordic countries have a high prevalence of multiple sclerosis, and to further explore the genetic background of the disease, we have carried out a genome-wide screen for linkage in 136 sibling-pairs with multiple sclerosis from Denmark, Finland, Norway and Sweden by typing 399 microsatellite markers. Seventeen regions where the lod score exceeds the nominal 5% significance threshold (0.7) were identified-1q11-24, 2q24-32, 3p26.3, 3q21.1, 4q12, 6p25.3, 6p21-22, 6q21, 9q34.3, 10p15, 10p12-13, 11p15.5, 12q21.3, 16p13.3, 17q25.3, 22q12-13 and Xp22.3. Although none of these regions reaches the level of genome-wide significance, the number observed exceeds the 10 that would be expected by chance alone. Our results significantly add to the growing body of linkage data relating to multiple sclerosis.

Denmark↗

PubMed2002

The Wellcome trust UK-Irish bipolar affective disorder sibling-pair genome screen: first stage report.

We have completed the first stage of a two-stage genome wide screen designed to identify chromosomal regions that may harbour susceptibility genes for bipolar affective disorder. The first stage screening sample included 509 subjects from 151 nuclear families recruited within the United Kingdom and Republic of Ireland. This sample contained 154 narrowly defined affected sibling pairs (DSM-IV BPI) and 258 broadly defined affected sibling pairs (DSM-IV BPI, SABP, BPII, BPNOS or MDD(R)), approximately two thirds of all families contained at least one other additional typed individual. All individuals were genotyped using 398 highly polymorphic microsatellite markers from Applied Biosystems's Linkage Mapping Set Version 2. The average inter-marker distance was 9.6 cM and the mean heterozygosity was 0.78. Analysis of these data using non-parametric linkage methods (MAPMAKER/SIBS) found no evidence for loci of major effect and no regions reached genome-wide significance for either suggestive or significant linkage. We identified 19 points across the genome where the MLS exceeded a value set for follow up in our second stage screen (MLS > or = 0.74 (equivalent to a nominal pointwise significance of 5%) under the narrowest diagnostic model). These points were on chromosomes 2, 3, 4, 6, 7, 9, 10, 12, 17, 18 & X. Some of these points overlapped with previous linkage reports both within bipolar affective disorder and other psychiatric illnesses. Under the narrowest diagnostic model, the single most significant multipoint linkage was on chromosome 18 at marker D18S452 (MLS=1.54). Overall the highest MLS was 1.70 on chromosome 2 at marker D2S125, under the broadest diagnostic model.

Adult↗

PubMed2002

Vitreoretinopathy with phalangeal epiphyseal dysplasia, a type II collagenopathy resulting from a novel mutation in the C-propeptide region of the molecule.

A large family with dominantly inherited rhegmatogenous retinal detachment, premature arthropathy, and development of phalangeal epiphyseal dysplasia, resulting in brachydactyly was linked to COL2A1, the gene encoding proalpha1(II) collagen. Mutational analysis of the gene by exon sequencing identified a novel mutation in the C-propeptide region of the molecule. The glycine to aspartic acid change occurred in a region that is highly conserved in all fibrillar collagen molecules. The resulting phenotype does not fit easily into pre-existing subgroups of the type II collagenopathies, which includes spondyloepiphyseal dysplasia, and the Kniest, Strudwick, and Stickler dysplasias.

Adult↗

PubMed2001

Likelihood-ratio affected sib-pair tests applied to multiply affected sibships: issues of power and type I error rate.

"All-pairs" likelihood-ratio analyses, such as those performed by MAPMAKER/SIBS [Kruglyak and Lander, 1995], require that a sibship containing N affected siblings be split into N(N - 1)/2 sibships, each containing a different pair of affected sibs, before analysis. Each of these N(N - 1)/2 sibships may also contain the other affected sibs from the original sibship, coded as unaffected, to infer missing parental genotypes, as is done automatically in MAPMAKER/SIBS. Then, the use of the same individuals both as affecteds to test for linkage and, elsewhere, as unaffecteds to infer missing parental genotypes leads to negative correlations in the estimated identity by descent sharing among affected pairs from the same original multiplex sibship. This gives a conservative test of linkage, even when no downweighting is applied. Conversely, if the other affected sibs from the original sibship are omitted, the correlations are positive and the linkage test is anticonservative in the absence of weighting. True type I error probability also depends on marker informativity, typed parents, number of affected sibs included in the analysis, and the weighting scheme. This suggests the use of simulation, rather than asymptotic theory, to assess significance levels. The power of multiplex sibships relative to affected pairs increases with increasing phenocopy percentage, but the presence of typed unaffected sibs improves the relative power of multiplex sibships greatly only when penetrance is high. It was found that the 2/N weighting proposed by Suarez and Hodge [1979] increased power over an unweighted analysis in many situations, provided significance levels were adjusted appropriately by simulation.

Computer Simulation↗

PubMed2000

Susceptibility locus for Alzheimer's disease on chromosome 10.

The apolipoprotein E (APOE) gene is the only genetic risk factor that has so far been linked to risk for late-onset Alzheimer's disease (LOAD). However, 50 percent of Alzheimer's disease cases do not carry an APOE4 allele, suggesting that other risk factors must exist. We performed a two-stage genome-wide screen in sibling pairs with LOAD to detect other susceptibility loci. Here we report evidence for an Alzheimer's disease locus on chromosome 10. Our stage one multipoint lod score (logarithm of the odds ratio for linkage/no linkage) of 2.48 (266 sibling pairs) increased to 3.83 in stage 2 (429 sibling pairs) close to D10S1225 (79 centimorgans). This locus modifies risk for Alzheimer's disease independent of APOE genotype.

Age of Onset↗

PubMed2000

Multicenter linkage study of schizophrenia candidate regions on chromosomes 5q, 6q, 10p, and 13q: schizophrenia linkage collaborative group III.

Schizophrenia candidate regions 33-51 cM in length on chromosomes 5q, 6q, 10p, and 13q were investigated for genetic linkage with mapped markers with an average spacing of 5.64 cM. We studied 734 informative multiplex pedigrees (824 independent affected sibling pairs [ASPs], or 1,003 ASPs when all possible pairs are counted), which were collected in eight centers. Cases with diagnoses of schizophrenia or schizoaffective disorder (DSM-IIIR criteria) were considered affected (n=1,937). Data were analyzed with multipoint methods, including nonparametric linkage (NPL), ASP analysis using the possible-triangle method, and logistic-regression analysis of identity-by-descent (IBD) sharing in ASPs with sample as a covariate, in a test for intersample heterogeneity and for linkage with allowance for intersample heterogeneity. The data most supportive for linkage to schizophrenia were from chromosome 6q; logistic-regression analysis of linkage allowing for intersample heterogeneity produced an empirical P value <.0002 with, or P=.0004 without, inclusion of the sample that produced the first positive report in this region; the maximum NPL score in this region was 2.47 (P=.0046), the maximum LOD score (MLS) from ASP analysis was 3.10 (empirical P=.0036), and there was significant evidence for intersample heterogeneity (empirical P=.0038). More-modest support for linkage was observed for chromosome 10p, with logistic-regression analysis of linkage producing an empirical P=. 045 and with significant evidence for intersample heterogeneity (empirical P=.0096).

Chromosome Mapping↗

PubMed2000

Clustering methods applied to allele sharing data.

Here we focus on using clustering methods to disentangle the interacting factors that lead to the presentation of complex diseases. Relative pairs are placed in discrete subgroups, or classes, based upon their pattern of allele sharing at a sequence of markers and on concomitant risk factors. The relationship between the locus information and the affectation status of the relative pairs within each subgroup then can be assessed. Cluster analysis (CLA) and latent class analysis (LCA) were applied to sibling allele sharing data from GAW11 simulated data, and to an existing Alzheimer's disease (AD) dataset. Both methods were able to identify markers linked to all 3 disease loci in the GAW11 data. LCA and CLA also replicated regions of chromosomes identified in an analysis of the AD data using affected-sib-pair methods. These analyses indicate that classification tools may be useful for detecting susceptibility genes for complex traits.

Aged↗

PubMed2000

Detailed genotyping demonstrates association between the slow acetylator genotype for N-acetyltransferase 2 (NAT2) and familial Parkinson's disease.

In a preliminary report we demonstrated an association between the slow acetylator genotype of N-acetyltransferase 2 (NAT2) and familial cases of Parkinson's disease (FPD). Using a considerably more precise NAT2 typing method, which detects all mutant NAT2 alleles with a frequency of >1% in the white population, we have now retyped all the original patients and control subjects to investigate the reliability of our initial findings. The slow acetylator genotype remained considerably more common among FPD (73%) than normal control subjects (NPC, 43%) or the disease (Huntington's disease [HD]) control group (52%) with an odds ratio (OR) of 3.58 (95% confidence interval (CI): 1.96-6.56; p = 0.00003) for FPD versus NPC and an OR of 2.50 (95% CI: 1.37-4.56, p = 0.003) for FPD versus HD. Furthermore, the wild-type allele 4 conferred a protective effect with an OR of 0.39 (95% CI: 0.23-0.64; p = 0.0025) for FPD versus NPC and an OR of 0.50 (95% CI: 0.30-0.85, p = 0.01) for FPD versus HD. The results of this study support an association between the NAT2 slow acetylator genotype and FPD in our population.

Acetylation↗

PubMed1999

Genetic variability at the amyloid-beta precursor protein locus may contribute to the risk of late-onset Alzheimer's disease.

In a series of sibpairs with late onset Alzheimer's disease, we have examined the segregation of the loci involved in the early onset, autosomal dominant form of the disorder by using flanking microsatellite repeat markers: thus we have used APP-PCR3 and D21S210 to examine the segregation of the amyloid-beta precursor protein (APP) gene, the markers DI 4S77 and D14S284 to examine the segregation of the presenilin 1 (PSI) gene and the markers D1S227, D1S249 and D1S419 to examine the segregation of presenilin 2 (PS2). We carried out our analyses on the whole dataset of 291 affected sibpairs, and on subsets comprising those sibpairs in which neither had an apolipoprotein E4 allele (65 affected sibpairs) and those in which both had an apolipoprotein E4 allele (165 affected sibpairs). We used the programs SPLINK to generate allele frequencies and MAPMAKER/SIBS to analyze our results. We examined the segregation of the markers D19S908 and D19S918 that are close to the apolipoprotein E (ApoE) gene as a positive control to assess whether the methods we are employing have the capability to identify known loci. The sibpair approach to the identification of genetic risk loci is relatively insensitive as indicated by the failure of the ApoE locus to reach statistical significance (P = 0.06). Nevertheless, these data suggest that neither the PS1 nor the PS2 gene is a major locus for late-onset AD, but that the APP gene cannot be ruled out as a risk locus in those sibships without an E4 allele (P = 0.014). The possibility that APP is indeed a locus for late onset disease will need confirmation in other series of familial cases.

Age of Onset↗