Biomedical subjects

James D Malley

Publications and source records attributed to James D Malley.

17 recordsLinked to original sources

PubMed2006

Global analysis of X-chromosome dosage compensation.

BACKGROUND: Drosophila melanogaster females have two X chromosomes and two autosome sets (XX;AA), while males have a single X chromosome and two autosome sets (X;AA). Drosophila male somatic cells compensate for a single copy of the X chromosome by deploying male-specific-lethal (MSL) complexes that increase transcription from the X chromosome. Male germ cells lack MSL complexes, indicating that either germline X-chromosome dosage compensation is MSL-independent, or that germ cells do not carry out dosage compensation. RESULTS: To investigate whether dosage compensation occurs in germ cells, we directly assayed X-chromosome transcripts using DNA microarrays and show equivalent expression in XX;AA and X;AA germline tissues. In X;AA germ cells, expression from the single X chromosome is about twice that of a single autosome. This mechanism ensures balanced X-chromosome expression between the sexes and, more importantly, it ensures balanced expression between the single X chromosome and the autosome set. Oddly, the inactivation of an X chromosome in mammalian females reduces the effective X-chromosome dose and means that females face the same X-chromosome transcript deficiency as males. Contrary to most current dosage-compensation models, we also show increased X-chromosome expression in X;AA and XX;AA somatic cells of Caenorhabditis elegans and mice. CONCLUSION: Drosophila germ cells compensate for X-chromosome dose. This occurs by equilibrating X-chromosome and autosome expression in X;AA cells. Increased expression of the X chromosome in X;AA individuals appears to be phylogenetically conserved.

Animals↗

PubMed2006

Short-term prediction of mortality in patients with systemic lupus erythematosus: classification of outcomes using random forests.

OBJECTIVE: To identify demographic and clinical characteristics that classify patients with systemic lupus erythematosus (SLE) at risk for in-hospital mortality. METHODS: Patients hospitalized in California from 1996 to 2000 with a principal diagnosis of SLE (N = 3,839) were identified from a state hospitalization database. As candidate predictors of mortality, we used patient demographic characteristics; the presence or absence of 40 different clinical conditions listed among the discharge diagnoses; and 2 summary indexes derived from the discharge diagnoses, the Charlson Index and the SLE Comorbidity Index. Predictors of patients at increased risk of mortality were identified and validated using random forests, a statistical procedure that is a generalization of single classification trees. Random forests use bootstrapped samples of patients and randomly selected subsets of predictors to create individual classification trees, and this process is repeated to generate multiple trees (a forest). Classification is then done by majority vote across all trees. RESULTS: Of the 3,839 patients, 109 died during hospitalization. Selecting from all available predictors, the random forests had excellent predictive accuracy for classification of death. The mean classification error rate, averaged over 10 forests of 500 trees each, was 11.9%. The most important predictors were the Charlson Index, respiratory failure, SLE Comorbidity Index, age, sepsis, nephritis, and thrombocytopenia. CONCLUSION: Information on clinical diagnoses can be used to accurately predict mortality among hospitalized patients with SLE. Random forests represent a useful technique to identify the most important predictors from a larger (often much larger) number and to validate the classification.

Adult↗

PubMed2006

HLA polymorphisms in African Americans with idiopathic inflammatory myopathy: allelic profiles distinguish patients with different clinical phenotypes and myositis autoantibodies.

OBJECTIVE: To investigate possible associations of HLA polymorphisms with idiopathic inflammatory myopathy (IIM) in African Americans, and to compare this with HLA associations in European American IIM patients with IIM. METHODS: Molecular genetic analyses of HLA-A, B, Cw, DRB1, and DQA1 polymorphisms were performed in a large population of African American patients with IIM (n = 262) in whom the major clinical and autoantibody subgroups were represented. These data were compared with similar information previously obtained from European American patients with IIM (n = 571). RESULTS: In contrast to European American patients with IIM, African American patients with IIM, in particular those with polymyositis, had no strong disease associations with HLA alleles of the 8.1 ancestral haplotype; however, African Americans with dermatomyositis or with anti-Jo-1 autoantibodies shared the risk factor HLA-DRB1*0301 with European Americans. We detected novel HLA risk factors in African American patients with myositis overlap (DRB1*08) and in African American patients producing anti-signal recognition particle (DQA1*0102) and anti-Mi-2 autoantibodies (DRB1*0302). DRB1*0302 and the European American-, anti-Mi-2-associated risk factor DRB1*0701 were found to share a 4-amino-acid sequence motif, which was predicted by comparative homology analyses to have identical 3-dimensional orientations within the peptide-binding groove. CONCLUSION: These data demonstrate that North American IIM patients from different ethnic groups have both shared and distinct immunogenetic susceptibility factors, depending on the clinical phenotype. These findings, obtained from the largest cohort of North American minority patients with IIM studied to date, add additional support to the hypothesis that the myositis syndromes comprise multiple, distinct disease entities, perhaps arising from divergent pathogenic mechanisms and/or different gene-environment interactions.

Adenosine Triphosphatases↗

PubMed2006

Immunogenetic risk and protective factors for juvenile dermatomyositis in Caucasians.

OBJECTIVE: To define the relative importance (RI) of class II major histocompatibility complex (MHC) alleles and peptide binding motifs as risk or protective factors for juvenile dermatomyositis (DM), and to compare these with HLA associations in adult DM. METHODS: DRB1 and DQA1 typing was performed in 142 Caucasian patients with juvenile DM, and the results were compared with HLA typing data from 193 patients with adult DM and 797 race-matched controls. Random Forests classification and multiple logistic regression were used to assess the RI of the HLA associations. RESULTS: The HLA-DRB1*0301 allele was a primary risk factor (odds ratio [OR] 3.9), while DQA1*0301 (OR 2.8), DQA1*0501 (OR 2.1), and homozygosity for DQA1*0501 (OR 3.2) were additional risk factors for juvenile DM. These risk factors were not present in patients with adult DM without defined autoantibodies. DQA1 alleles *0201 (OR 0.37), *0101 (OR 0.38), and *0102 (OR 0.51) were identified as novel protective factors for juvenile DM, the latter 2 also being protective factors in adult DM. The peptide binding motif DRB1 (9)EYSTS(13) was a risk factor, and DQA1 motifs F(25), S(26), and (45)(V/A)W(R/K)(47) were protective. Random Forests classification analysis revealed that among the identified risk factors for juvenile DM, DRB1*0301 had a higher RI (100%) than DQA1*0301 (RI 57%), DQA1*0501 (RI 42%), or the peptide binding motifs. In a logistic regression model, DRB1*0301 and DQA1*0201 were the strongest risk and protective factors, respectively, for juvenile DM. CONCLUSION: DRB1*0301 is ranked higher in RI than DQA1*0501 as a risk factor for juvenile DM. DQA1*0301 is a newly identified HLA risk factor for juvenile DM, while 3 of the DQA1 alleles studied are newly identified protective factors for juvenile DM.

Adolescent↗

PubMed2006

Immunogenetic risk and protective factors for the idiopathic inflammatory myopathies: distinct HLA-A, -B, -Cw, -DRB1, and -DQA1 allelic profiles distinguish European American patients with different myositis autoantibodies.

The idiopathic inflammatory myopathies (IIM) are systemic connective tissue diseases defined by chronic muscle inflammation and weakness associated with autoimmunity. We have performed low to high resolution molecular typing to assess the genetic variability of major histocompatibility complex loci (HLA-A, -B, -Cw, -DRB1, and -DQA1) in a large population of European American patients with IIM (n = 571) representing the major myositis autoantibody groups. We established that alleles of the 8.1 ancestral haplotype (8.1 AH) are important risk factors for the development of IIM in patients producing anti-synthetase/anti-Jo-1, -La, -PM/Scl, and -Ro autoantibodies. Moreover, a random forests classification analysis suggested that 8.1 AH-associated alleles B*0801 and DRB1*0301 are the principal HLA risk markers. In addition, we have identified several novel HLA susceptibility factors associated distinctively with particular myositis-specific (MSA) and myositis-associated autoantibody (MAA) groups of the IIM. IIM patients with anti-PL-7 (anti-threonyl-tRNA synthetase) autoantibodies have a unique HLA Class I risk allele, Cw*0304 (pcorr = 0.046), and lack the 8.1 AH markers associated with other anti-synthetase autoantibodies (for example, anti-Jo-1 and anti-PL-12). In addition, HLA-B*5001 and DQA1*0104 are novel potential risk factors among anti-signal recognition particle autoantibody-positive IIM patients (pcorr = 0.024 and p = 0.010, respectively). Among those patients with MAA, HLA DRB1*11 and DQA1*06 alleles were identified as risk factors for myositis patients with anti-Ku (pcorr = 0.041) and anti-La (pcorr = 0.023) autoantibodies, respectively. Amino acid sequence analysis of the HLA DRB1 third hypervariable region identified a consensus motif, 70D (hydrophilic)/71R (basic)/74A (hydrophobic), conferring protection among patients producing anti-synthetase/anti-Jo-1 and -PM/Scl autoantibodies. Together, these data demonstrate that HLA signatures, comprising both risk and protective alleles or motifs, distinguish IIM patients with different myositis autoantibodies and may have diagnostic and pathogenic implications. Variations in associated polymorphisms for these immune response genes may reflect divergent pathogenic mechanisms and/or responses to unique environmental triggers in different groups of subjects resulting in the heterogeneous syndromes of the IIM.

Alleles↗

PubMed2006

Cytokine profile in PFAPA syndrome suggests continuous inflammation and reduced anti-inflammatory response.

PFAPA syndrome is characterized by periodic episodes of high fever, aphthous stomatitis, pharyngitis, and/or cervical adenitis. It is of unknown etiology and manifests usually before 5 years of age. We determined serum and intracellular cytokine levels in six PFAPA patients (4 males, 2 females, mean age 8 years (+/- 1.2 SEM), range 4-13) during the symptom-free period as well as 6-12 hours and 18-24 hours after fever onset. Values were compared to age-matched, healthy controls. Febrile PFAPA attacks led to a significant increase in IL-6 and IFN-gamma serum concentrations compared to symptom-free periods and to controls, with IL-1beta, TNF-alpha and IL-12p70 levels being significantly higher than in controls. Lymphocytic IFN-gamma and CD8+ IL-2 production was consistently significantly elevated compared to healthy children. During the asymptomatic period, serum concentrations of IL-1beta, IL-6, TNF-alpha and IL-12p70 were significantly increased compared to controls. Intracellular TNF-alpha synthesis was not elevated at any time point. Soluble TNFRp55 levels were even lower in between febrile episodes, reaching values comparable to controls during attacks, whereas soluble TNFRp75 levels increased during attacks compared to healthy children. Anti-inflammatory IL-4 in serum was at all times lower in PFAPA patients compared to controls with no difference in levels of intracellular IL-4 and IL-10 or serum IL-10. The observed increase of pro-inflammatory mediators, even between febrile attacks, suggests a dysregulation of the immune response in PFAPA syndrome, with continuous pro-inflammatory cytokine activation and a reduced anti-inflammatory response.

Adolescent↗

PubMed2005

Support vector machines committee classification method for computer-aided polyp detection in CT colonography.

RATIONALE AND OBJECTIVES: A new classification scheme for the computer-aided detection of colonic polyps in computed tomographic colonography is proposed. MATERIALS AND METHODS: The scheme involves an ensemble of support vector machines (SVMs) for classification, a smoothed leave-one-out (SLOO) cross-validation method for obtaining error estimates, and use of a bootstrap aggregation method for training and model selection. Our use of an ensemble of SVM classifiers with bagging (bootstrap aggregation), built on different feature subsets, is intended to improve classification performance compared with single SVMs and reduce the number of false-positive detections. The bootstrap-based model-selection technique is used for tuning SVM parameters. In our first experiment, two independent data sets were used: the first, for feature and model selection, and the second, for testing to evaluate the generalizability of our model. In the second experiment, the test set that contained higher resolution data was used for training and testing (using the SLOO method) to compare SVM committee and single SVM performance. RESULTS: The overall sensitivity on independent test set was 75%, with 1.5 false-positive detections/study, compared with 76%-78% sensitivity and 4.5 false-positive detections/study estimated using the SLOO method on the training set. The sensitivity of the SVM ensemble retrained on the former test set estimated using the SLOO method was 81%, which is 7%-10% greater than the sensitivity of a single SVM. The number of false-positive detections per study was 2.6, a 1.5 times reduction compared with a single SVM. CONCLUSION: Training an SVM ensemble on one data set and testing it on the independent data has shown that the SVM committee classification method has good generalizability and achieves high sensitivity and a low false-positive rate. The model selection and improved error estimation method are effective for computer-aided polyp detection.

Algorithms↗

PubMed2005

Immunogenetic risk and protective factors for the idiopathic inflammatory myopathies: distinct HLA-A, -B, -Cw, -DRB1 and -DQA1 allelic profiles and motifs define clinicopathologic groups in caucasians.

The idiopathic inflammatory myopathies (IIM) are systemic connective tissue diseases in which autoimmune pathology is suspected to promote chronic muscle inflammation and weakness. We have performed low to high resolution genotyping to characterize the allelic profiles of HLA-A, -B, -Cw, -DRB1, and -DQA1 loci in a large population of North American Caucasian patients with IIM representing the major clinicopathologic groups (n = 571). We confirmed that alleles of the 8.1 ancestral haplotype were important risk markers for the development of IIM, and a random forests classification analysis suggested that within this haplotype, HLA-B*0801, DRB1*0301 and/ or closely linked genes are the principal HLA risk factors. In addition, we identified several novel HLA factors associated distinctly with 1 or more clinicopathologic groups of IIM. The DQA1*0201 allele and associated peptide-binding motif (KLPLFHRL) were exclusive protective factors for the CD8+ T cell-mediated IIM forms of polymyositis (PM) and inclusion body myositis (IBM) (pc < 0.005). In contrast, HLA-A*68 alleles were significant risk factors for dermatomyositis (DM) (pc = 0.0021), a distinct clinical group thought to involve a humorally mediated immunopathology. While the DQA1*0301 allele was detected as a possible risk factor for IIM, PM, and DM patients (p < 0.05), DQA1*03 alleles were protective factors for IBM (pc = 0.0002). Myositis associated with malignancies was the most distinctive group of IIM wherein HLA Class I alleles were the only identifiable susceptibility factors and a shared HLA-Cw peptide-binding motif (AGSHTLQWM) conferred significant risk (pc = 0.019). Together, these data suggest that HLA susceptibility markers distinguish different myositis phenotypes with divergent pathogenetic mechanisms. These variations in associated HLA polymorphisms may reflect responses to unique environmental triggers resulting in the tissue pathospecificity and distinct clinicopathologic syndromes of the IIM.

Adult↗

PubMed2003

Multiple neural network classification scheme for detection of colonic polyps in CT colonography data sets.

RATIONALE AND OBJECTIVES: A new classification system for colonic polyp detection, designed to increase sensitivity and reduce the number of false-positive findings with computed tomographic colonography, was developed and tested in this study. MATERIALS AND METHODS: The system involves classification by a committee of neural networks (NNs), each using largely distinct subsets of features selected from a general set. Back-propagation NNs trained with the Levenberg-Marquardt algorithm were used as primary classifiers (committee members). The set of features included region density, Gaussian and mean curvature and sphericity, lesion size, colon wall thickness, and the means and standard deviations of all of these values. Subsets of variables were initially selected because of their effectiveness according to training and test sample misclassification rates. The final decision for each case is based on the majority vote across the networks and reflects the weighted votes of all networks. The authors also introduce a smoothed cross-validation method designed to improve estimation of the true misclassification rates by reducing bias and variance. RESULTS: This committee method reduced the false-positive rate by 36%, a clinically meaningful reduction, and improved sensitivity by an average of 6.9% compared with decisions made by any single NN. The overall sensitivity and specificity were 82.9% and 95.3%, respectively, when sensitivity was estimated by means of smoothed cross-validation. CONCLUSION: The proposed method of using multiple classifiers and majority voting is recommended for classification tasks with large sets of input features, particularly when selected feature subsets may not be equally effective and do not provide satisfactory true- and false-positive rates. This approach reduces variance in estimates of misclassification rates.

Algorithms↗

PubMed2003

Autobiographical memory in schizophrenia: an examination of the distribution of memories.

Patients with schizophrenia display numerous memory impairments. Examination of autobiographical memory distribution across the life span can constrain theories of how schizophrenia affects memory. Previously, schizophrenic patients were shown to produce fewer memories from early adulthood than from childhood or the recent past (A. Feinstein, T. E. Goldberg, B. Nowlin, & D. R. Weinberger, 1998), this temporal paucity corresponding with illness onset. The current study examined this issue further using a different (noncued) method. Age-matched schizophrenic patients (n = 21) and controls (n = 21) were to freely generate 50 episodes, after which they dated these memories. Patients generated fewer memories than did controls, especially from the recent decade. When the overall lower production of memories was controlled for, the groups displayed equivalent recency effects. It was concluded that patients' paucity of memories generated from the recent decade reflects encoding or acquisition problems, which may be associated with the illness period.

Adult↗

PubMed2003

Computer-assisted detection of colonic polyps with CT colonography using neural networks and binary classification trees.

Detection of colonic polyps in CT colonography is problematic due to complexities of polyp shape and the surface of the normal colon. Published results indicate the feasibility of computer-aided detection of polyps but better classifiers are needed to improve specificity. In this paper we compare the classification results of two approaches: neural networks and recursive binary trees. As our starting point we collect surface geometry information from three-dimensional reconstruction of the colon, followed by a filter based on selected variables such as region density, Gaussian and average curvature and sphericity. The filter returns sites that are candidate polyps, based on earlier work using detection thresholds, to which the neural nets or the binary trees are applied. A data set of 39 polyps from 3 to 25 mm in size was used in our investigation. For both neural net and binary trees we use tenfold cross-validation to better estimate the true error rates. The backpropagation neural net with one hidden layer trained with Levenberg-Marquardt algorithm achieved the best results: sensitivity 90% and specificity 95% with 16 false positives per study.

Algorithms↗

PubMed2002

New genes involved in cancer identified by retroviral tagging.

Retroviral insertional mutagenesis in BXH2 and AKXD mice induces a high incidence of myeloid leukemia and B- and T-cell lymphoma, respectively. The retroviral integration sites (RISs) in these tumors thus provide powerful genetic tags for the discovery of genes involved in cancer. Here we report the first large-scale use of retroviral tagging for cancer gene discovery in the post-genome era. Using high throughput inverse PCR, we cloned and analyzed the sequences of 884 RISs from a tumor panel composed primarily of B-cell lymphomas. We then compared these sequences, and another 415 RIS sequences previously cloned from BXH2 myeloid leukemias and from a few AKXD lymphomas, against the recently assembled mouse genome sequence. These studies identified 152 loci that are targets of retroviral integration in more than one tumor (common retroviral integration sites, CISs) and therefore likely to encode a cancer gene. Thirty-six CISs encode genes that are known or predicted to be genes involved in human cancer or their homologs, whereas others encode candidate genes that have not yet been examined for a role in human cancer. Our studies demonstrate the power of retroviral tagging for cancer gene discovery in the post-genome era and indicate a largely unrecognized complexity in mouse and presumably human cancer.

Animals↗

PubMed2002

Comparison of vaccine strategies using recombinant env-gag-pol MVA with or without an oligomeric Env protein boost in the SHIV rhesus macaque model.

Rhesus macaques were immunized with a replication-deficient vaccinia virus (MVA) expressing human immunodeficiency virus type 1 89.6 envelope (env) and SIV gagpol (MVA/SHIV89.6) with or without a protein boost consisting of soluble 89.6 env (gp140). Immunization with MVA/SHIV89.6 alone elicited binding antibodies in all animals and neutralizing antibodies in 5 of 15 animals. Both types of antibodies were enhanced by protein boosting. In addition, CD8 cells exhibiting CM9 tetramer binding were detected in the subset of animals that were Mamu-A*01 positive. Animals were challenged intravenously with either SHIV-89.6 (Study 1) or the more pathogenic derivative SHIV-89.6P (Study 2). In Study 1, all control and vaccinated animals except one became infected. However, the levels of viremia were as follows: controls > rMVA alone > rMVA + protein. The differences were statistically significant between immunized and control groups but not between the two immunized groups. In Study 2, all animals became infected; however, the vaccinated group exhibited a 5-fold reduction in peak viremia and a 10-fold reduction in the postacute phase viremia in comparison to the controls. All of the controls required euthanasia by 10 months after challenge. A relationship between vaccine-induced antibody titers and reduction in virus burden was observed in both studies. Thus, immunization with MVA/SHIV89.6 alone or with a protein boost stimulated both arms of the immune system and resulted in significant control of viremia and delayed progression to disease after challenge with SHIV-89.6P.

AIDS Vaccines↗

PubMed2002

Differences in idiopathic inflammatory myopathy phenotypes and genotypes between Mesoamerican Mestizos and North American Caucasians: ethnogeographic influences in the genetics and clinical expression of myositis.

OBJECTIVE: As part of a larger, worldwide study of the ethnogeography of myositis, we evaluated the clinical, serologic, and immunogenetic features of Mestizo (Mexican and Guatemalan) and North American Caucasian patients with idiopathic inflammatory myopathy (IIM). METHODS: Clinical manifestations, autoantibodies, HLA-DRB1 and DQA1 alleles, and immunoglobulin Gm/Km allotypes were compared between 138 Mestizos with IIM and 287 Caucasians with IIM, using the same classification criteria and standardized questionnaires. RESULTS: IIM in Mestizo patients was characterized by a higher proportion of dermatomyositis (69% of adult Mestizos versus 35% of adult Caucasians; P < 0.001) and anti-Mi-2 autoantibodies (30% versus 7% of adults, respectively, and 32% versus 4% of children, respectively; P < 0.01). Genetic risk factors also differed in these populations. Whereas Mestizos had no HLA risk factors for IIM, HLA-DRB1*0301, the linked allele DQA1*0501, and DRB1 alleles sharing the first hypervariable region motif (9)EYSTS(13) were major risk factors in Caucasian patients with IIM. Furthermore, different HLA-DRB1 and DQA1 alleles were associated with anti-Mi-2 autoantibodies (DRB1*04 and DQA1*03 in Mestizos and DRB1*07 and DQA1*02 in Caucasians). Immunoglobulin gamma-chain allotypes Gm(1), Gm(17) (odds ratio for both 11.3, P = 0.008), and Gm(21) (odds ratio 7.3, P = 0.005) and kappa-chain allotype Km(3) (odds ratio 7.3, P = 0.005) were risk factors for IIM in Mestizos; however, no Gm or Km allotypes were risk or protective factors in Caucasians. In addition, Gm and Km phenotypes were unique risk factors (Gm 1,3,17 5,13,21 and Gm 1,17 23 21 and Km 3,3) or protective factors (Km 1,1) for the development of myositis and anti-Mi-2 autoantibodies (Gm 1,2,3,17 23 5,13,21) in adult Mestizos. CONCLUSION: IIM in Mesoamerican Mestizos differs from IIM in North American Caucasians in the frequency of phenotypic features and in the immune-response genes predisposing to and protecting from myositis and anti-Mi-2 autoantibodies at 4 chromosomal loci. These and other data suggest the likelihood that the expression of IIM is modulated by different genes and environmental exposures around the world.

Adult↗

PubMed2002

Colonic polyps: complementary role of computer-aided detection in CT colonography.

PURPOSE: To apply a computer-aided detection (CAD) algorithm to supine and prone multisection helical computed tomographic (CT) colonographic images to confirm if there is any added benefit provided by CAD over that of standard clinical interpretation. MATERIALS AND METHODS: CT colonography (with patients in both supine and prone positions) was performed with a multisection helical CT scanner in 40 asymptomatic high-risk patients. There were two consecutive series of patients, 20 of whom had at least one polyp 1.0 cm in size or larger and 20 of whom had normal colons at conventional colonoscopy performed the same day. The CT colonographic images were interpreted with an automated CAD algorithm and by two radiologists who were blinded to colonoscopy findings. RESULTS: For 25 polyps at least 1.0 cm in size ("large" polyps), sensitivity for detection by at least one radiologist was 48% (12 of 25). The sensitivity of CAD for detecting large polyps was also 48% (12 of 25), but the CAD algorithm detected four of 13 large polyps that were not detected by either radiologist (31%, 95% two-sided CI: 9, 61), increasing the potential sensitivity to 64% (16 of 25). For polyps identifiable retrospectively, sensitivity of CAD was 67% (12 of 18), and sensitivity of the combination of detection with the CAD algorithm or by at least one radiologist was 89% (16 of 18). There were an average of 11 false-positive detections per patient for CAD. CONCLUSION: In this series of patients in whom radiologists had difficulties detecting polyps (compared with sensitivities of 75%-90% reported in the literature), this CAD algorithm played a complementary role to conventional interpretation of CT colonographic images by detecting a number of large polyps missed by trained observers.

Aged↗

PubMed2002

A comprehensive method for genome scans.

In applications involving the use of genome scans the problem of correcting for multiple testing figures prominently. A frequently used approach is the Bonferroni adjustment, but this is known to be often severely conservative. As an alternative we use the method of importance sampling to accurately and efficiently obtain required exceedance probabilities. This method is comprehensive in the sense that it has application to exceedance probabilities for other classes of test statistics, such as those for linkage disequilibrium or Hardy-Weinberg equilibrium at multiple loci. We illustrate the importance sampling technique by focusing on affected sib pair tests done at a large number of fully informative markers. We demonstrate how our approach can be used to obtain exceedance probabilities for arbitrary marker spacings, and we compare our approach with that of Feingold et al. [1993], which uses the method of large deviations and does not provide the means for adjusting for unequal marker spacing.

Genetic Linkage↗

PubMedDate not supplied

Habit and skill learning in schizophrenia: evidence of normal striatal processing with abnormal cortical input.

Different forms of nondeclarative learning involve regionally specific striatal circuits. The motor circuit (involving the putamen) has been associated with motor-skill learning and the dorsolateral prefrontal cortex (DLPFC) circuit (involving the caudate) has been associated with cognitive-habit learning. Efforts to differentiate functional striatal circuits within patient samples have been limited. Previous studies have provided mixed results regarding striatal-dependent nondeclarative learning deficits in patients with schizophrenia. In this study, a cognitive-habit learning task (probabilistic weather prediction) was used to assess the DLPFC circuit and a motor-skill learning task (pursuit rotor) was used to assess the motor circuit in 35 patients with schizophrenia and 35 normal controls. Patients with schizophrenia displayed significant performance differences from controls on both nondeclarative tasks; however, cognitive-habit learning rate in patients did not differ from controls. There were performance and learning-rate differences on the motor-skill learning task between the whole sample of patients and controls, however, analysis of a subset of patients and controls matched on general intellectual level eliminated learning rate differences between groups. The abnormal performance offset between patients with schizophrenia and controls in the absence of learning rate differences suggests that abnormal cortical processing provides altered input to normal striatal circuitry.

Adult↗