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Classification and regression tree and spatial analyses reveal geographic heterogeneity in genome wide linkage study of Indian visceral leishmaniasis.

ABSTRACT: Genome wide linkage studies (GWLS) have provided evidence for loci controlling visceral leishmaniasis on Chromosomes 1p22, 6q27, 22q12 in Sudan and 6q27, 9p21, 17q11-q21 in Brazil. Genome wide studies from the major focus of disease in India have not previously been reported.We undertook a GWLS in India in which a primary ?10 cM (515 microsatellites) scan was carried out in 58 multicase pedigrees (74 nuclear families; 176 affected, 353 total individuals) and replication sought in 79 pedigrees (102 nuclear families; 218 affected, 473 total individuals). The primary scan provided evidence (?2 adjacent markers allele-sharing LOD?0.59; nominal P?0.05) for linkage on Chromosomes 2, 5, 6, 7, 8, 10, 11, 20 and X, with peaks at 6p25.3-p24.3 and 8p23.1-p21.3 contributed to largely by 31 Hindu families and at Xq21.1-q26.1 by 27 Muslim families. Refined mapping confirmed linkage across all primary scan families at 2q12.2-q14.1 and 11q13.2-q23.3, but only 11q13.2-q23.3 replicated (combined LOD?=?1.59; P?=?0.0034). Linkage at 6p25.3-p24.3 and 8p23.1-p21.3, and at Xq21.1-q26.1, was confirmed by refined mapping for primary Hindu and Muslim families, respectively, but only Xq21.1-q26.1 replicated across all Muslim families (combined LOD 1.49; P?=?0.0045). STRUCTURE and SMARTPCA did not identify population genetic substructure related to religious group. Classification and regression tree, and spatial interpolation, analyses confirm geographical heterogeneity for linkages at 6p25.3-p24.3, 8p23.1-p21.3 and Xq21.1-q26.1, with specific clusters of families contributing LOD scores of 2.13 (P?=?0.0009), 1.75 (P?=?0.002) and 1.84 (P?=?0.001), respectively.GWLS has identified novel loci that show geographical heterogeneity in their influence on susceptibility to VL in India.

SUBMITTER: Fakiola M

PROVIDER: S-EPMC3013125 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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Classification and regression tree and spatial analyses reveal geographic heterogeneity in genome wide linkage study of Indian visceral leishmaniasis.

Fakiola Michaela M Mishra Anshuman A Rai Madhukar M Singh Shri Prakash SP O'Leary Rebecca A RA Ball Stephen S Francis Richard W RW Firth Martin J MJ Radford Ben T BT Miller E Nancy EN Sundar Shyam S Blackwell Jenefer M JM

PloS one 20101231 12

<h4>Background</h4>Genome wide linkage studies (GWLS) have provided evidence for loci controlling visceral leishmaniasis on Chromosomes 1p22, 6q27, 22q12 in Sudan and 6q27, 9p21, 17q11-q21 in Brazil. Genome wide studies from the major focus of disease in India have not previously been reported.<h4>Methods and findings</h4>We undertook a GWLS in India in which a primary ∼10 cM (515 microsatellites) scan was carried out in 58 multicase pedigrees (74 nuclear families; 176 affected, 353 total indivi ...[more]

PMID: 21209823

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Project description:BACKGROUND:Visceral leishmaniasis (VL) is a deadly parasitic diseases caused by Leishmania donovani; it is a major health problem in many countries. A lack of proper understanding of the disease biology, poor diagnostic methods and increasing drug resistance are the main reasons for the growing burden of VL infection. Comparative plasma proteomics are a relatively useful technique that can be used to investigate disease-associated alterations that can help in understanding host responses against pathogens, and might be useful in disease management and diagnosis. RESULT:In this study, a comparative proteomics and glycoproteomics approach using 2DE and 2D-DIGE was employed between early diagnosed VL patients of all age groups and healthy endemic and non-endemic controls in order to aid the recognition of disease-associated alterations in host plasma. Comparative proteomics was performed by the depletion of seven highly abundant plasma proteins. Comparative glycoproteomics was performed by the depletion of albumin and IgG, followed by purification of plasma glycoproteins using a multi lectin affinity column. From these two approaches, 39 differentially expressed protein spots were identified and sequenced using MALDI-TOF/TOF mass spectrometry. This revealed ten distinct proteins that appeared in multiple spots, suggesting micro-heterogeneity. Among these proteins, alpha-1-antitrypsin, alpha-1-B glycoprotein and amyloid-A1 precursor were up-regulated, whereas vitamin-D binding protein, apolipoprotein-A-I and transthyretin were down-regulated in VL. Alterations in the levels of these proteins in VL-infected plasma were further confirmed by western blot and ELISA. CONCLUSIONS:These proteins may be involved in the survival of parasites, resisting neutrophil elastase, and in their multiplication in macrophages, potentially maintaining endogenous anti-inflammatory and immunosuppressive conditions. Consequently, the results of this study may help in understanding the host response against L.donovani, which could help in the discovery of new drugs and disease management. Finally, these alterations on protein levels might be beneficial in improving early diagnosis considering those as biomarkers in Indian VL.

Project description:BackgroundVisceral leishmaniasis (VL) is a multifactorial disease, where the host genetics play a significant role in determining the disease outcome. The immunological role of anti-inflammatory cytokine, Interleukin 10 (IL10), has been well-documented in parasite infections and considered as a key regulatory cytokine for VL. Although VL patients in India display high level of IL10 in blood serum, no genetic study has been conducted to assess the VL susceptibility / resistance. Therefore, the aim of this study is to investigate the role of IL10 variations in Indian VL; and to estimate the distribution of disease associated allele in diverse Indian populations.MethodologyAll the exons and exon-intron boundaries of IL10 were sequenced in 184 VL patients along with 172 ethnically matched controls from VL endemic region of India.Result and discussionOur analysis revealed four variations; rs1518111 (2195 A>G, intron), rs1554286 (2607 C>T, intron), rs3024496 (4976 T>C, 3' UTR) and rs3024498 (5311 A>G, 3' UTR). Of these, a variant g.5311A is significantly associated with VL (χ2=18.87; p =0.00001). In silico approaches have shown that a putative micro RNA binding site (miR-4321) is lost in rs3024498 mRNA. Further, analysis of the above four variations in 1138 individuals from 34 ethnic populations, representing different social and linguistic groups who are inhabited in different geographical regions of India, showed variable frequency. Interestingly, we have found, majority of the tribal populations have low frequency of VL ('A' of rs3024498); and high frequency of leprosy ('T' of rs1554286), and Behcet's ('A' of rs1518111) associated alleles, whereas these were vice versa in castes. Our findings suggest that majority of tribal populations of India carry the protected / less severe allele against VL, while risk / more severe allele for leprosy and Behcet's disease. This study has potential implications in counseling and management of VL and other infectious diseases.

Project description:BackgroundIn the typical setting of gene-selection problems from high-dimensional data, e.g., gene expression data from microarray or next-generation sequencing-based technologies, an enormous volume of high-throughput data is generated, and there is often a need for a simple, computationally-inexpensive, non-parametric screening procedure than can quickly and accurately find a low-dimensional variable subset that preserves biological information from the original very high-dimensional data (dimension p > 40,000). This is in contrast to the very sophisticated variable selection methods that are computationally expensive, need pre-processing routines, and often require calibration of priors.ResultsWe present a tree-based sequential CART (S-CART) approach to variable selection in the binary classification setting and compare it against the more sophisticated procedures using simulated and real biological data. In simulated data, we analyze S-CART performance versus (i) a random forest (RF), (ii) a fully-parametric Bayesian stochastic search variable selection (SSVS), and (iii) the moderated t-test statistic from the LIMMA package in R. The simulation study is based on a hierarchical Bayesian model, where dataset dimensionality, percentage of significant variables, and substructure via dependency vary. Selection efficacy is measured through false-discovery and missed-discovery rates. In all scenarios, the S-CART method is seen to consistently outperform SSVS and RF in both speed and detection accuracy. We demonstrate the utility of the S-CART technique both on simulated data and in a control-treatment mouse study. We show that the network analysis based on the S-CART-selected gene subset in essence recapitulates the biological findings of the study using only a fraction of the original set of genes considered in the study's analysis.ConclusionsThe relatively simple-minded gene selection algorithms like S-CART may often in practical circumstances be preferred over much more sophisticated ones. The advantage of the "greedy" selection methods utilized by S-CART and the likes is that they scale well with the problem size and require virtually no tuning or training while remaining efficient in extracting the relevant information from microarray-like datasets containing large number of redundant or irrelevant variables.AvailabilityThe MATLAB 7.4b code for the S-CART implementation is available for download from https://neyman.mcg.edu/posts/scart.zip.

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Classification and regression tree and spatial analyses reveal geographic heterogeneity in genome wide linkage study of Indian visceral leishmaniasis.

Publications

Classification and regression tree and spatial analyses reveal geographic heterogeneity in genome wide linkage study of Indian visceral leishmaniasis.

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