Identification of neuroglycan C and interacting partners as potential susceptibility genes for schizophrenia in a Southern Chinese population.

Chromosome 3p was reported by previous studies as one of the regions showing strong evidence of linkage with schizophrenia. We performed a fine-mapping association study of a 6-Mb high-LD and gene-rich region on 3p in a Southern Chinese sample of 489 schizophrenia patients and 519 controls to search for susceptibility genes. In the initial screen, 4 SNPs out of the 144 tag SNPs genotyped were nominally significant (P < 0.05). One of the most significant SNPs (rs3732530, P = 0.0048) was a non-synonymous SNP in the neuroglycan C (NGC, also known as CSPG5) gene, which belongs to the neuregulin family. The gene prioritization program Endeavor ranked NGC 8th out of the 129 genes in the 6-Mb region and the highest among the genes within the same LD block. Further genotyping of NGC revealed 3 more SNPs to be nominally associated with schizophrenia. Three other genes (NRG1, ErbB3, ErbB4) involved in the neuregulin pathways were subsequently genotyped. Interaction analysis by multifactor dimensionality reduction (MDR) revealed a significant two-SNP interaction between NGC and NRG1 (P = 0.015) and three-SNP interactions between NRG1 and ErbB4 (P = 0.009). The gene NGC is exclusively expressed in the brain. It is implicated in neurodevelopment in rats and was previously shown to promote neurite outgrowth. Methamphetamine, a drug that may induce psychotic symptoms, was reported to alter the expression of NGC. Taken together, these results suggest that NGC may be a novel candidate gene, and neuregulin signaling pathways may play an important role in schizophrenia.

Toward the proteomic identification of biomarkers for the prediction of HBV related hepatocellular carcinoma.

Early detection is a key step for effective intervention of hepatocellular carcinoma (HCC), the lack of sensitive and specific biomarkers is a major reason for the high rate of HCC-related mortality. This report described an integrated strategy by combining SELDI-ProteinChip, sophisticated algorithm analysis, acetonitrile (ACN) pre-treatment and two-dimensional electrophoresis (2DE)-peptide mass fingerprinting (PMF) techniques to identify serological markers for the prediction of HBV-related HCC. Proteomic profiling of three groups of serum specimens from HBV-related HCC (50 cases), HBV infection (45 cases), and normal subjects (30 cases) was conducted by using SELDI-ProteinChip system and the resulting different protein peaks were subjected to stepwise statistical analyses. Three most discriminatory peaks at 5890, 11615, and 11724 Da, respectively, were screened out from the statistical algorithm and a predictive model based on the three peaks was constructed and tested using the newly enrolled serum samples. 2DE was applied to separate and compare the serum samples that were pre-treated by ACN precipitation. The protein spots obviously intensified in HCC sera in the 2DE region of 12 kDa were identified by PMF to be serum SAA, which was validated by SELDI-TOF spectra of HCC sera after immunoprecipitation using anti-SAA antibody and by Western blot experiments. Given the fact that SAA is not a specific biomarker, further attempt is being made to identify the other two most discriminatory peaks to realize the possibility of using the predictive model for HCC surveillance and prediction.

High-throughput loss-of-heterozygosity study of chromosome 3p in lung cancer using single-nucleotide polymorphism markers.

Loss of DNA copy number at the short arm of chromosome 3 is one of the most common genetic changes in human lung cancer, suggesting the existence of one or more tumor suppressor genes (TSG) at 3p. To identify most frequently deleted regions and candidate TSGs within these regions, a recently developed single-nucleotide polymorphism (SNP)-mass spectrometry-genotyping (SMSG) technology was applied to investigate the loss of heterozygosity (LOH) in 30 primary non-small-cell lung cancers. A total of 386 SNP markers that spanned a region of 70 Mb at 3p, from 3pter to 3p14.1, were selected for LOH analysis. The average intermarker distance in the present study is approximately 180 kb. Several frequently deleted regions, including 3p26.3, 3p25.3, 3p24.1, 3p23, and 3p21.1, were found. Several candidate TSGs within these frequently detected LOH regions have been found, including APG7L at 3p25.3, CLASP2 at 3p23, and CACNA2D3 at 3p21.1. This study also showed that SMSG technology is a very useful approach to rapidly define the minimal deleted region and to identify target TSGs in a given cancer.

T-1213C polymorphism of estrogen receptor beta is associated with low bone mineral density and osteoporotic fractures.

Osteoporosis is a complex disease with a strong genetic component, but the genes involved are poorly defined. To determine whether estrogen receptor beta (ESR2) gene is an osteoporosis risk gene, we examined its association with bone mineral density (BMD) and fracture risk. Using a gene-based approach, a set of 12 polymorphisms of ESR2 was studied in 752 case-control pairs of southern Chinese in ethnicity. Among all polymorphisms, the most significant relation with BMD and fracture risk was observed with T-1213C. Subjects with low BMD had a higher frequency of the variant C allele of T-1213C (cases 11.4%, control 8.4%, P = 0.02). The C allele was associated with 4% reduction in BMD at both the spine and hip in women, and 11% reduction in spine BMD and 9% reduction in hip BMD in men. Similar results were seen with SNP haplotype analysis. Subjects with the C allele of T-1213C were associated with higher risks of osteoporosis and BMD T scores < or = -2.5 (odds ratios: 2.2 at spine and 3.5 at femoral neck for women; 3.5 at lumbar spine for men). Postmenopausal women carrying this C allele were associated with 2.22-fold increased risk of osteoporotic fractures (95% confidence interval 1.26-4.25) even after adjusting for BMD. In conclusion, ESR2 is involved in BMD determination in both sexes. The T-1213C polymorphism influences the risk of fracture in postmenopausal women independent of BMD.

Toward personalized medicine in the neuropsychiatric field.

There are great expectations for the personalized medicine approach to address the therapeutic needs of patients in the twenty-first century. Advances in human genome science and molecular innovations in neuroscience have encouraged the pharmaceutical industry to focus beyond broad spectrum population therapeutics--the driving force behind the "blockbuster" product concept--to personalized medicine. For central nervous system (CNS) therapeutics, repeated failures in converting scientific discoveries to clinical trial successes and regulatory approvals have precipitated a drug pipeline crisis and eroded confidence in the industry. This chapter describes how innovations in genomics and translational medicine can impact the future of neuropsychiatry and deconvolute the complexity of psychiatric diseases from symptoms biology. A targeted and consistent investment is needed to restore confidence in translating science into clinical success.

Genome-wide pharmacogenetics of antidepressant response in the GENDEP project.

OBJECTIVE: The purpose of this study was to identify genetic variants underlying the considerable individual differences in response to antidepressant treatment. The authors performed a genome-wide association analysis of improvement of depression severity with two antidepressant drugs. METHOD: High-quality Illumina Human610-quad chip genotyping data were available for 706 unrelated participants of European ancestry treated for major depression with escitalopram (N=394) or nortriptyline (N=312) over a 12-week period in the Genome-Based Therapeutic Drugs for Depression (GENDEP) project, a partially randomized open-label pharmacogenetic trial. RESULTS: Single nucleotide polymorphisms in two intergenic regions containing copy number variants on chromosomes 1 and 10 were associated with the outcome of treatment with escitalopram or nortriptyline at suggestive levels of significance and with a high posterior likelihood of true association. Drug-specific analyses revealed a genome-wide significant association between marker rs2500535 in the uronyl 2-sulphotransferase gene and response to nortriptyline. Response to escitalopram was best predicted by a marker in the interleukin-11 (IL11) gene. A set of 72 a priori-selected candidate genes did not show pharmacogenetic associations above a chance level, but an association with response to escitalopram was detected in the interleukin-6 gene, which is a close homologue of IL11. CONCLUSIONS: While limited statistical power means that a number of true associations may have been missed, these results suggest that efficacy of antidepressants may be predicted by genetic markers other than traditional candidates. Genome-wide studies, if properly replicated, may thus be important steps in the elucidation of the genetic basis of pharmacological response.

Meta-analysis of linkage studies for Alzheimer's disease--a web resource.

Familial late-onset Alzheimer's disease (LOAD) shows high heritability. However, with the exception of ApoE, no well-replicated susceptibility genes have been identified to date. Several genome-wide linkage studies have nominated potential susceptibility loci but results are inconsistent, with individual scans showing few significant LOD scores. We have pooled linkage results from five independent genome scans and used the genome search meta-analysis (GSMA) method to analyse these data. The combined sample results in 2206 affected individuals and 785 families from Caucasian and Caribbean Hispanic ethnicities. The Caucasian samples included subjects from the US, the Netherlands and Sweden. Genome-wide suggestive evidence for linkage was observed on chromosomes 1p13.3-q31.1, 7pter-p21.1 and 8p22-p21.1 in the weighted GSMA analysis. The chromosome 8p region achieved the lowest summed rank p-value of 0.001. We also identified seven loci with nominally significant evidence for linkage to 3q12.3-q22.1, 6p21.1-q15, 7p14.1-q21.11, 17q24.3-qter and 19p13.3-qter. The GSMA finding suggests that these loci may harbour susceptibility genes for LOAD. We have also developed a web resource (http://alzres.iop.kcl.ac.uk/) to present additional GSMA analyses with different study selection criteria, facilitate the reanalysis of genome-wide linkage data and provide open access to the GSMA data.

Data acquisition for meta-analysis of genome-wide linkage studies using the genome search meta-analysis method.

BACKGROUND: The Genome Search Meta-Analysis (GSMA) method enables researchers to pool results across genome-wide linkage studies, to increase the power to detect linkage. RESULTS from individual studies must be extracted, with the maximum evidence for linkage placed into bins, usually of 30 cM width, and ranked within the study. Ranks are then summed across studies, with high summed ranks potentially showing evidence for linkage in the meta-analysis. OBJECTIVES: In this paper we study the properties of the GSMA method considering two different issues: (1) data binning from genome-wide results when indexed markers or graphs are available, based on either predefined boundary markers, or equal-length bins; (2) the use of selected instead of genome-wide results, using simulation to estimate power and type I error rates of GSMA. This is relevant when published papers show only summary results (e.g. with NPL score >1). RESULTS: Using digitizing software to extract linkage statistics from graphs and assigning equal bin length is accurate, with the resulting ranking of bins similar to those defined through boundary markers. Simulation results show that power can fall substantially when genome-wide results are not available, particularly when only results from a single marker are available in a linked region. However there is no increase in false positive findings. CONCLUSIONS: The GSMA method is robust across different bin definitions and methods of data presentation and extraction. Using studies based on only the top ranked bins does not produce false positive results, but lacks power to detect genes conferring a modest increase in risk. Therefore, we advise that effort should be made to obtain genome-wide results from investigators or from published papers to avoid limiting the utility of the GSMA.

Confirmation of linkage to chromosome 1q for spine bone mineral density in southern Chinese.

Chromosome 1q has previously been linked to bone mineral density (BMD) variation in the general population in several genome-wide linkage studies in both humans and mouse model. The aim of present study is to replicate and fine map the QTL influencing BMD in chromosome 1q in southern Chinese. Twelve microsatellite markers were genotyped for a 57 cMu region in the chromosome 1q in 306 southern Chinese families with 1,459 subjects. Each of these families was ascertained through a proband with BMD Z-scores less than -1.3 at the hip or spine. BMD (g/cm2) at the L1-4 lumbar spine, femoral neck (FN), trochanter and total hip was measured by dual-energy X-ray absortiometry. Linkage analyses were performed using the variance component linkage analysis method implemented in Merlin software. Four markers (D1S2878, D1S196, D1S452, and D1S218) achieved a LOD score greater than 1.0 with spine BMD, with the maximum multipoint LOD score of 2.36 at the marker D1S196. We did not detect a LOD score greater than 1.0 for BMD at the FN, trochanter, or total hip in multipoint linkage analyses. Our results present the first evidence for the presence of an osteoporosis susceptibility gene on chromosome 1q in non-Caucasian subjects. Further analyses of candidate genes are warranted to identify QTL genes and variants underlying the variations of BMD in this region.

Identification of two sex-specific quantitative trait loci in chromosome 11q for hip bone mineral density in Chinese.

BACKGROUND: Chromosome 11q has not only been found to contain mutations responsible for the several Mendelian disorders of the skeleton, but it has also been linked to bone mineral density (BMD) variation in several genome-wide linkage studies. Furthermore, quantitative trait loci (QTL) affecting BMD in inbred mice and baboons have been mapped to a region syntenic to human chromosome 11q. The aim of the present study is to determine whether there is a QTL for BMD variation on chromosome 11q in the Chinese population. METHODS: Nineteen microsatellite markers were genotyped for a 75 cM region on 11q13-25 in 306 Chinese families with 1,459 subjects. BMD (g/cm(2)) was measured by DXA. Linkage analyses were performed using the variance component linkage analysis method implemented in Merlin software. RESULTS: For women, a maximum LOD score of 1.62 was achieved at 90.8 cM on 11q21 near the marker D11S4175 for femoral neck BMD; LOD scores greater than 1.0 were observed on 11q13 for trochanter BMD. For men, a maximum LOD score of 1.57 was achieved at 135.8 cM on 11q24 near the marker D11S4126 for total hip BMD. CONCLUSION: We have not only replicated the previous linkage finding on chromosome 11q but also identified two sex-specific QTL that contribute to BMD variation in Chinese women and men.

Assessment of linkage and association of 13 genetic loci with bone mineral density.

Bone mineral density (BMD), an important risk factor for osteoporosis, is a complex trait likely affected by multiple genes. The linkage and/or association of 13 polymorphic loci of seven candidate genes (estrogen receptor alpha [ERalpha] and beta [ERbeta], calcium-sensing receptor, vitamin D receptor, collagen type 1alpha1, low-density lipoprotein [LDL] receptor-related protein 5 [LRPS], and transforming growth factor beta1) were evaluated in 177 southern Chinese pedigrees of 674 subjects, with each pedigree identified through a proband having a BMD Z score of -1.28 or less at the hip or spine. A suggestive linkage was detected between the IVS1-351A/G polymorphism of ERalpha and spine BMD, and between the 1082G/A, 1730G/A, and D14S1026 polymorphisms of ERbeta and BMD at both spine and hip. The quantitative transmission disequilibrium test (QTDT) detected total family association between 1730G/A of ERbeta and BMD at spine and hip; between D14S1026 of ERbeta and hip BMD; and between the 266A/G and 2220C/T polymorphisms of LRP5 and hip BMD. Similar total family associations were detected when only the females were analyzed. In addition, the IVS1-397T/C polymorphism of ERalpha was associated with spine BMD, and the 266A/G and 2220C/T polymorphisms of LRP5 were associated with femoral neck BMD in the females. A within-family association was detected with the IVS1-397T/C polymorphism of ERalpha, and the 266A/G and 2220C/T polymorphisms of LRP5 in the females. The effect of each polymorphism on BMD variance ranged from 1% to 4%. In conclusion, ERalpha, ERbeta and LRP5 are important candidate genes determining BMD variation, especially in females.