Gene-Based Association Analysis Identified Novel Genes Associated with Bone Mineral Density

Genetic factors contribute to the variation of bone mineral density (BMD), which is a major risk factor of osteoporosis. The aim of this study was to identify more “novel” genes for BMD. Based on the publicly available SNP-based P values, we performed an initial gene-based analysis in a total of 32,961 individuals. Furthermore, we performed differential expression, pathway and protein-protein interaction analyses to find supplementary evidence to support the significance of the identified genes. About 21,695 genes for femoral neck (FN)-BMD and 21,683 genes for lumbar spine (LS)-BMD were analyzed using gene-based association analysis. A total of 35 FN-BMD associated genes and 53 LS-BMD associated genes were identified (P < 2.3×10^-6) after Bonferroni correction. Among them, 64 genes have not been reported in previous SNP-based genome-wide association studies. Differential expression analysis further supported the significant associations of 14 genes with FN-BMD and 19 genes with LS-BMD. Especially, WNT3 and WNT9B in the Wnt signaling pathway for FN-BMD were further supported by pathway analysis and protein-protein interaction analysis. The present study took the advantage of gene-based association method to perform a supplementary analysis of the GWAS dataset and found some BMD-associated genes. The evidence taken together supported the importance of Wnt signaling pathway genes in determining osteoporosis. Our findings provided more insights into the genetic basis of osteoporosis.     

A Genome-Wide Association Study Confirms VKORC1, CYP2C9, and CYP4F2 as Principal Genetic Determinants of Warfarin Dose

We report the first genome-wide association study (GWAS) whose sample size (1,053 Swedish subjects) is sufficiently powered to detect genome-wide significance (p<1.5×10⁻⁷) for polymorphisms that modestly alter therapeutic warfarin dose. The anticoagulant drug warfarin is widely prescribed for reducing the risk of stroke, thrombosis, pulmonary embolism, and coronary malfunction. However, Caucasians vary widely (20-fold) in the dose needed for therapeutic anticoagulation, and hence prescribed doses may be too low (risking serious illness) or too high (risking severe bleeding). Prior work established that ~30% of the dose variance is explained by single nucleotide polymorphisms (SNPs) in the warfarin drug target VKORC1 and another ~12% by two non-synonymous SNPs (*2, *3) in the cytochrome P450 warfarin-metabolizing gene CYP2C9. We initially tested each of 325,997 GWAS SNPs for association with warfarin dose by univariate regression and found the strongest statistical signals (p<10⁻⁷⁸) at SNPs clustering near VKORC1 and the second lowest p-values (p<10⁻³¹) emanating from CYP2C9. No other SNPs approached genome-wide significance. To enhance detection of weaker effects, we conducted multiple regression adjusting for known influences on warfarin dose (VKORC1, CYP2C9, age, gender) and identified a single SNP (rs2108622) with genome-wide significance (p=8.3×10⁻¹⁰) that alters protein coding of the CYP4F2 gene. We confirmed this result in 588 additional Swedish patients (p<0.0029) and, during our investigation, a second group provided independent confirmation from a scan of warfarin-metabolizing genes. We also thoroughly investigated copy number variations, haplotypes, and imputed SNPs, but found no additional highly significant warfarin associations. We present power analysis of our GWAS that is generalizable to other studies, and conclude we had 80% power to detect genome-wide significance for common causative variants or markers explaining at least 1.5% of dose variance. These GWAS results provide further impetus for conducting large-scale trials assessing patient benefit from genotype-based forecasting of warfarin dose.     

How Genome-Wide SNP-SNP Interactions Relate to Nasopharyngeal Carcinoma Susceptibility

This study is the first to use genome-wide association study (GWAS) data to evaluate the multidimensional genetic architecture underlying nasopharyngeal cancer. Since analysis of data from GWAS confirms a close and consistent association between elevated risk for nasopharyngeal carcinoma (NPC) and major histocompatibility complex class 1 genes, our goal here was to explore lesser effects of gene-gene interactions. We conducted an exhaustive genome-wide analysis of GWAS data of NPC, revealing two-locus interactions occurring between single nucleotide polymorphisms (SNPs), and identified a number of suggestive interaction loci which were missed by traditional GWAS analyses. Although none of the interaction pairs we identified passed the genome-wide Bonferroni-adjusted threshold for significance, using independent GWAS data from the same population (Stage 2), we selected 66 SNP pairs in 39 clusters with P<0.01. We identified that in several chromosome regions, multiple suggestive interactions group to form a block-like signal, effectively reducing the rate of false discovery. The strongest cluster of interactions involved the CREB5 gene and a SNP rs1607979 on chromosome 17q22 (P = 9.86×10⁻¹¹) which also show trans-expression quantitative loci (eQTL) association in Chinese population. We then detected a complicated cis-interaction pattern around the NPC-associated HLA-B locus, which is immediately adjacent to copy-number variations implicated in male susceptibility for NPC. While it remains to be seen exactly how and to what degree SNP-SNP interactions such as these affect susceptibility for nasopharyngeal cancer, future research on these questions holds great promise for increasing our understanding of this disease’s genetic etiology, and possibly also that of other gene-related cancers.     

Transcriptome Profiling of Human Ulcerative Colitis Mucosa Reveals Altered Expression of Pathways Enriched in Genetic Susceptibility Loci

Human colonic mucosa altered by inflammation due to ulcerative colitis (UC) displays a drastically altered pattern of gene expression compared with healthy tissue. We aimed to understand the underlying molecular pathways influencing these differences by analyzing three publically-available, independently-generated microarray datasets of gene expression from endoscopic biopsies of the colon. Gene set enrichment analysis (GSEA) revealed that all three datasets share 87 gene sets upregulated in UC lesions and 8 gene sets downregulated (false discovery rate <0.05). The upregulated pathways were dominated by gene sets involved in immune function and signaling, as well as the control of mitosis. We applied pathway analysis to genotype data derived from genome-wide association studies (GWAS) of UC, consisting of 5,584 cases and 11,587 controls assembled from eight European-ancestry cohorts. The upregulated pathways derived from the gene expression data showed a highly significant overlap with pathways derived from the genotype data (33 of 56 gene sets, hypergeometric P = 1.49×10^–19). This study supports the hypothesis that heritable variation in gene expression as measured by GWAS signals can influence key pathways in the development of disease, and that comparison of genetic susceptibility loci with gene expression signatures can differentiate key drivers of inflammation from secondary effects on gene expression of the inflammatory process.     

Genome-Wide Scan Identifies Variant in TNFSF13 Associated with Serum IgM in a Healthy Chinese Male Population

IgM provides a first line of defense during microbial infections. Serum IgM levels are detected routinely in clinical practice. And IgM is a genetically complex trait. We conducted a two-stage genome-wide association study (GWAS) to identify genetic variants affecting serum IgM levels in a Chinese population of 3495, including 1999 unrelated subjects in the first stage and 1496 independent individuals in the second stage. Our data show that a common single nucleotide polymorphism (SNP), rs11552708 located in the TNFSF13 gene was significantly associated with IgM levels (p = 5.00×10⁻⁷ in first stage, p = 1.34×10⁻³ in second stage, and p = 4.22×10⁻⁹ when combined). Besides, smoking was identified to be associated with IgM levels in both stages (P<0.05), but there was no significant interaction between smoking and the identified SNP (P>0.05). It is suggested that TNFSF13 may be a susceptibility gene affecting serum IgM levels in Chinese male population.     

Pathway Analysis Based on a Genome-Wide Association Study of Polycystic Ovary Syndrome

Background

Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in women of reproductive age, and it is affected by both environmental and genetic factors. Although the genetic component of PCOS is evident, studies aiming to identify susceptibility genes have shown controversial results. This study conducted a pathway-based analysis using a dataset obtained through a genome-wide association study (GWAS) to elucidate the biological pathways that contribute to PCOS susceptibility and the associated genes.

Methods

We used GWAS data on 636,797 autosomal single nucleotide polymorphisms (SNPs) from 1,221 individuals (432 PCOS patients and 789 controls) for analysis. A pathway analysis was conducted using meta-analysis gene-set enrichment of variant associations (MAGENTA). Top-ranking pathways or gene sets associated with PCOS were identified, and significant genes within the pathways were analyzed.

Results

The pathway analysis of the GWAS dataset identified significant pathways related to oocyte meiosis and the regulation of insulin secretion by acetylcholine and free fatty acids (all nominal gene-set enrichment analysis (GSEA) P-values < 0.05). In addition, INS, GNAQ, STXBP1, PLCB3, PLCB2, SMC3 and PLCZ1 were significant genes observed within the biological pathways (all gene P-values < 0.05).

Conclusions

By applying MAGENTA pathway analysis to PCOS GWAS data, we identified significant pathways and candidate genes involved in PCOS. Our findings may provide new leads for understanding the mechanisms underlying the development of PCOS.     

Blood cis-eQTL Analysis Fails to Identify Novel Association Signals among Sub-Threshold Candidates from Genome-Wide Association Studies in Restless Legs Syndrome

Restless legs syndrome (RLS) is a common neurologic disorder characterized by nightly dysesthesias affecting the legs primarily during periods of rest and relieved by movement. RLS is a complex genetic disease and susceptibility factors in six genomic regions have been identified by means of genome-wide association studies (GWAS). For some complex genetic traits, expression quantitative trait loci (eQTLs) are enriched among trait-associated single nucleotide polymorphisms (SNPs). With the aim of identifying new genetic susceptibility factors for RLS, we assessed the 332 best-associated SNPs from the genome-wide phase of the to date largest RLS GWAS for cis-eQTL effects in peripheral blood from individuals of European descent. In 740 individuals belonging to the KORA general population cohort, 52 cis-eQTLs with p_nominal<10⁻³ were identified, while in 976 individuals belonging to the SHIP-TREND general population study 53 cis-eQTLs with p_nominal<10⁻³ were present. 23 of these cis-eQTLs overlapped between the two cohorts. Subsequently, the twelve of the 23 cis-eQTL SNPs, which were not located at an already published RLS-associated locus, were tested for association in 2449 RLS cases and 1462 controls. The top SNP, located in the DET1 gene, was nominally significant (p<0.05) but did not withstand correction for multiple testing (p = 0.42). Although a similar approach has been used successfully with regard to other complex diseases, we were unable to identify new genetic susceptibility factor for RLS by adding this novel level of functional assessment to RLS GWAS data.     

Insights into Pancreatic Cancer Etiology from Pathway Analysis of Genome-Wide Association Study Data

Background

Pancreatic cancer is the fourth leading cause of cancer death in the U.S. and the etiology of this highly lethal disease has not been well defined. To identify genetic susceptibility factors for pancreatic cancer, we conducted pathway analysis of genome-wide association study (GWAS) data in 3,141 pancreatic cancer patients and 3,367 controls with European ancestry.

Methods

Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways identified from the Kyoto Encyclopedia of Genes and Genomes database. We used the logistic kernel machine (LKM) test to identify major contributing genes to each pathway. We conducted functional enrichment analysis of the most significant genes (P<0.01) using the Database for Annotation, Visualization, and Integrated Discovery (DAVID).

Results

Two pathways were significantly associated with risk of pancreatic cancer after adjusting for multiple comparisons (P<0.00025) and in replication testing: neuroactive ligand-receptor interaction, (Ps<0.00002), and the olfactory transduction pathway (P = 0.0001). LKM test identified four genes that were significantly associated with risk of pancreatic cancer after Bonferroni correction (P<1×10⁻⁵): ABO, HNF1A, OR13C4, and SHH. Functional enrichment analysis using DAVID consistently found the G protein-coupled receptor signaling pathway (including both neuroactive ligand-receptor interaction and olfactory transduction pathways) to be the most significant pathway for pancreatic cancer risk in this study population.

Conclusion

These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer.     

Meta-Analysis of Genome-Wide Association Studies in African Americans Provides Insights into the Genetic Architecture of Type 2 Diabetes

Type 2 diabetes (T2D) is more prevalent in African Americans than in Europeans. However, little is known about the genetic risk in African Americans despite the recent identification of more than 70 T2D loci primarily by genome-wide association studies (GWAS) in individuals of European ancestry. In order to investigate the genetic architecture of T2D in African Americans, the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium examined 17 GWAS on T2D comprising 8,284 cases and 15,543 controls in African Americans in stage 1 analysis. Single nucleotide polymorphisms (SNPs) association analysis was conducted in each study under the additive model after adjustment for age, sex, study site, and principal components. Meta-analysis of approximately 2.6 million genotyped and imputed SNPs in all studies was conducted using an inverse variance-weighted fixed effect model. Replications were performed to follow up 21 loci in up to 6,061 cases and 5,483 controls in African Americans, and 8,130 cases and 38,987 controls of European ancestry. We identified three known loci (TCF7L2, HMGA2 and KCNQ1) and two novel loci (HLA-B and INS-IGF2) at genome-wide significance (4.15×10⁻⁹⁴<P<5×10⁻⁸, odds ratio (OR) = 1.09 to 1.36). Fine-mapping revealed that 88 of 158 previously identified T2D or glucose homeostasis loci demonstrated nominal to highly significant association (2.2×10⁻²³ < locus-wide P<0.05). These novel and previously identified loci yielded a sibling relative risk of 1.19, explaining 17.5% of the phenotypic variance of T2D on the liability scale in African Americans. Overall, this study identified two novel susceptibility loci for T2D in African Americans. A substantial number of previously reported loci are transferable to African Americans after accounting for linkage disequilibrium, enabling fine mapping of causal variants in trans-ethnic meta-analysis studies.     

Targeting 160 Candidate Genes for Blood Pressure Regulation with a Genome-Wide Genotyping Array

The outcome of Genome-Wide Association Studies (GWAS) has challenged the field of blood pressure (BP) genetics as previous candidate genes have not been among the top loci in these scans. We used Affymetrix 500K genotyping data of KORA S3 cohort (n = 1,644; Southern-Germany) to address (i) SNP coverage in 160 BP candidate genes; (ii) the evidence for associations with BP traits in genome-wide and replication data, and haplotype analysis. In total, 160 gene regions (genic region±10 kb) covered 2,411 SNPs across 11.4 Mb. Marker densities in genes varied from 0 (n = 11) to 0.6 SNPs/kb. On average 52.5% of the HAPMAP SNPs per gene were captured. No evidence for association with BP was obtained for 1,449 tested SNPs. Considerable associations (P<10⁻³) were detected for the genes, where >50% of HAPMAP SNPs were tagged. In general, genes with higher marker density (>0.2 SNPs/kb) revealed a better chance to reach close to significance associations. Although, none of the detected P-values remained significant after Bonferroni correction (P<0.05/2319, P<2.15×10⁻⁵), the strength of some detected associations was close to this level: rs10889553 (LEPR) and systolic BP (SBP) (P = 4.5×10⁻⁵) as well as rs10954174 (LEP) and diastolic BP (DBP) (P = 5.20×10⁻⁵). In total, 12 markers in 7 genes (ADRA2A, LEP, LEPR, PTGER3, SLC2A1, SLC4A2, SLC8A1) revealed considerable association (P<10⁻³) either with SBP, DBP, and/or hypertension (HYP). None of these were confirmed in replication samples (KORA S4, HYPEST, BRIGHT). However, supportive evidence for the association of rs10889553 (LEPR) and rs11195419 (ADRA2A) with BP was obtained in meta-analysis across samples stratified either by body mass index, smoking or alcohol consumption. Haplotype analysis highlighted LEPR and PTGER3. In conclusion, the lack of associations in BP candidate genes may be attributed to inadequate marker coverage on the genome-wide arrays, small phenotypic effects of the loci and/or complex interaction with life-style and metabolic parameters.     

Genome-Wide Association Study Identifies GPC5 as a Novel Genetic Locus Protective against Sudden Cardiac Arrest

Background

Existing studies indicate a significant genetic component for sudden cardiac arrest (SCA) and genome-wide association studies (GWAS) provide an unbiased approach for identification of novel genes. We performed a GWAS to identify genetic determinants of SCA.

Methodology/Principal Findings

We used a case-control design within the ongoing Oregon Sudden Unexpected Death Study (Oregon-SUDS). Cases (n = 424) were SCAs with coronary artery disease (CAD) among residents of Portland, OR (2002–07, population ∼1,000,000) and controls (n = 226) were residents with CAD, but no history of SCA. All subjects were of White-European ancestry and GWAS was performed using Affymetrix 500K/5.0 and 6.0 arrays. High signal markers were genotyped in SCA cases (n = 521) identified from the Atherosclerosis Risk in Communities Study (ARIC) and the Cardiovascular Health Study (CHS) (combined n = 19,611). No SNPs reached genome-wide significance (p<5×10⁻⁸). SNPs at 6 loci were prioritized for follow-up primarily based on significance of p<10⁻⁴ and proximity to a known gene (CSMD2, GPR37L1, LIN9, B4GALNT3, GPC5, and ZNF592). The minor allele of GPC5 (GLYPICAN 5, rs3864180) was associated with a lower risk of SCA in Oregon-SUDS, an effect that was also observed in ARIC/CHS whites (p<0.05) and blacks (p<0.04). In a combined Cox proportional hazards model analysis that adjusted for race, the minor allele exhibited a hazard ratio of 0.85 (95% CI 0.74 to 0.98; p<0.01).

Conclusions/Significance

A novel genetic locus for SCA, GPC5, was identified from Oregon-SUDS and successfully validated in the ARIC and CHS cohorts. Three other members of the Glypican family have been previously implicated in human disease, including cardiac conditions. The mechanism of this specific association requires further study.     

Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on ¹H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10⁻⁸) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10⁻⁴⁴) and lysine (rs8101881, P = 1.2×10⁻³³), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn''s disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.     

Genome-Wide Association Study of Parity in Bangladeshi Women

Human fertility is a complex trait determined by gene-environment interactions in which genetic factors represent a significant component. To better understand inter-individual variability in fertility, we performed one of the first genome-wide association studies (GWAS) of common fertility phenotypes, lifetime number of pregnancies and number of children in a developing country population. The fertility phenotype data and DNA samples were obtained at baseline recruitment from individuals participating in a large prospective cohort study in Bangladesh. GWAS analyses of fertility phenotypes were conducted among 1,686 married women. One SNP on chromosome 4 was non-significantly associated with number of children at P <10^-7 and number of pregnancies at P <10^-6. This SNP is located in a region without a gene within 1 Mb. One SNP on chromosome 6 was non-significantly associated with extreme number of children at P <10^-6. The closest gene to this SNP is HDGFL1, a hepatoma-derived growth factor. When we excluded hormonal contraceptive users, a SNP on chromosome 5 was non-significantly associated at P <10^-5 for number of children and number of pregnancies. This SNP is located near C5orf64, an open reading frame, and ZSWIM6, a zinc ion binding gene. We also estimated the heritability of these phenotypes from our genotype data using GCTA (Genome-wide Complex Trait Analysis) for number of children (h_g ² = 0.149, SE = 0.24, p-value = 0.265) and number of pregnancies (h_g ² = 0.007, SE = 0.22, p-value = 0.487). Our genome-wide association study and heritability estimates of number of pregnancies and number of children in Bangladesh did not confer strong evidence of common variants for parity variation. However, our results suggest that future studies may want to consider the role of 3 notable SNPs in their analysis.     

Systematic Evaluation of Genetic Variants for Polycystic Ovary Syndrome in a Chinese Population

To date, eleven genome-wide significant (GWS) loci (P < 5×10⁻⁸) for polycystic ovary syndrome (PCOS) have been identified through genome-wide association studies (GWAS). Some of the risk loci have been selected for replications and validated in multiple ethnicities, however, few previous studies investigated all loci. Scanning all the GWAS variants would demonstrate a more informative profile of variance they explained. Thus, we analyzed all the 17 single nucleotide polymorphisms (SNPs) mapping to the 11 GWAS loci in an independent sample set of 800 Chinese subjects with PCOS and 1110 healthy controls systematically. Variants of rs3802457 in C9orf3 locus (P = 5.99×10⁻⁴) and rs13405728 in LHCGR locus (P = 3.73×10⁻⁴) were significantly associated with PCOS after the strict Bonferroni correction in our data set. The further haplotype analysis indicated that in the block of C9orf3 gene (rs4385527 and rs3802457), GA haplotype played a protective role in PCOS (8.7 vs 5.0, P = 9.85×10⁻⁶, OR = 0.548, 95%CI = 0.418–0.717), while GG haplotype was found suffering from an extraordinarily increased risk of PCOS (73.6% vs79.2%, P = 3.41×10⁻⁵, OR = 1.394, 95%CI = 1.191–1.632). Moreover, the directions of effects for all SNPs were consistent with previous GWAS reports (P = 1.53×10⁻⁵). Polygenic score analysis demonstrated that these 17 SNPs have a significant capacity on predicting case-control status in our samples (P = 7.17×10⁻⁹), meanwhile all these gathered 17 SNPs explained about 2.40% of variance. Our findings supported that C9orf3 and LHCGR loci variants were vital susceptibility of PCOS.     

Candidate Gene Association Analysis of Neuroblastoma in Chinese Children Strengthens the Role of LMO1

Neuroblastoma (NB) is the most common extra-cranial solid tumor in children and the most frequently diagnosed cancer in the first year of life. Previous genome-wide association studies (GWAS) of Caucasian and African populations have shown that common single nucleotide polymorphisms (SNPs) in several genes are associated with the risk of developing NB, while few studies have been performed on Chinese children. Herein, we examined the association between the genetic polymorphisms in candidate genes and the risk of NB in Chinese children. In total, 127 SNPs in nine target genes, revealed by GWAS studies of other ethnic groups and four related lincRNAs, were genotyped in 549 samples (244 NB patients and 305 healthy controls). After adjustment for gender and age, there were 21 SNPs associated with NB risk at the two-sided P < 0.05 level, 11 of which were located in LMO1. After correction for multiple comparisons, only rs204926 in LMO1 remained significantly different between cases and controls (OR = 0.45, 95% CI: 0.31–0.65, adjusted P = 0.003). In addition, 16 haplotypes in four separate genes were significantly different between case and control groups at an unadjusted P value < 0.05, 11 of which were located in LMO1. A major haplotype, ATC, containing rs204926, rs110420, and rs110419, conferred a significant increase in risk for NB (OR = 1.82, 95% CI: 1.41–2.36, adjusted P < 0.001). The major finding of our study was obtained for risk alleles within the LMO1 gene. Our data suggest that genetic variants in LMO1 are associated with increased NB risk in Chinese children.     

Connecting the Dots: Potential of Data Integration to Identify Regulatory SNPs in Late-Onset Alzheimer's Disease GWAS Findings

Late-onset Alzheimer''s disease (LOAD) is a multifactorial disorder with over twenty loci associated with disease risk. Given the number of genome-wide significant variants that fall outside of coding regions, it is possible that some of these variants alter some function of gene expression rather than tagging coding variants that alter protein structure and/or function. RegulomeDB is a database that annotates regulatory functions of genetic variants. In this study, we utilized RegulomeDB to investigate potential regulatory functions of lead single nucleotide polymorphisms (SNPs) identified in five genome-wide association studies (GWAS) of risk and age-at onset (AAO) of LOAD, as well as SNPs in LD (r²≥0.80) with the lead GWAS SNPs. Of a total 614 SNPs examined, 394 returned RegulomeDB scores of 1–6. Of those 394 variants, 34 showed strong evidence of regulatory function (RegulomeDB score <3), and only 3 of them were genome-wide significant SNPs (ZCWPW1/rs1476679, CLU/rs1532278 and ABCA7/rs3764650). This study further supports the assumption that some of the non-coding GWAS SNPs are true associations rather than tagged associations and demonstrates the application of RegulomeDB to GWAS data.     

Evidence for Association of Cell Adhesion Molecules Pathway and NLGN1 Polymorphisms with Schizophrenia in Chinese Han Population

Multiple risk variants of schizophrenia have been identified by Genome-wide association studies (GWAS). As a complement for GWAS, previous pathway-based analysis has indicated that cell adhesion molecules (CAMs) pathway might be involved in the pathogenesis of schizophrenia. However, less replication studies have been reported. Our objective was to investigate the association between CAMs pathway and schizophrenia in the Chinese Han population. We first performed a pathway analysis utilizing our previous GWAS data. The CAMs pathway (hsa04514) was significantly associated with schizophrenia using hybrid gene set-based test (P = 1.03×10⁻¹⁰) and hypergeometric test (P = 5.04×10⁻⁶). Moreover, 12 genes (HLA-A, HLA-C, HLA-DOB, HLA-DPB1, HLA-DQA2, HLA-DRB1, MPZ, CD276, NLGN1, NRCAM, CLDN1 and ICAM3) were modestly significantly associated with schizophrenia (P<0.01). Then, we selected one promising gene neuroligin 1 (NLGN1) to further investigate the association between eight significant SNPs and schizophrenia in an independent sample (1814 schizophrenia cases and 1487 healthy controls). Our study showed that seven SNPs of NLGN1 and two haplotype blocks were significantly associated with schizophrenia. This association was confirmed by the results of combined analysis. Among them, SNP rs9835385 had the most significant association with schizophrenia (P = 2.83×10⁻⁷). Furthermore, in silico analysis we demonstrated that NLGN1 is preferentially expressed in human brain and SNP rs1488547 was related to the expression level. We validated the association of CAMs pathway with schizophrenia in pathway-level and identified one susceptibility gene NLGN1. Further investigation of the roles of CAMs pathway in the pathogenesis of schizophrenia is warranted.     

Influence of Genetic Variation on Plasma Protein Levels in Older Adults Using a Multi-Analyte Panel

Proteins, widely studied as potential biomarkers, play important roles in numerous physiological functions and diseases. Genetic variation may modulate corresponding protein levels and point to the role of these variants in disease pathophysiology. Effects of individual single nucleotide polymorphisms (SNPs) within a gene were analyzed for corresponding plasma protein levels using genome-wide association study (GWAS) genotype data and proteomic panel data with 132 quality-controlled analytes from 521 Caucasian participants in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Linear regression analysis detected 112 significant (Bonferroni threshold p = 2.44×10⁻⁵) associations between 27 analytes and 112 SNPs. 107 out of these 112 associations were tested in the Indiana Memory and Aging Study (IMAS) cohort for replication and 50 associations were replicated at uncorrected p<0.05 in the same direction of effect as those in the ADNI. We identified multiple novel associations including the association of rs7517126 with plasma complement factor H-related protein 1 (CFHR1) level at p<1.46×10⁻⁶⁰, accounting for 40 percent of total variation of the protein level. We serendipitously found the association of rs6677604 with the same protein at p<9.29×10⁻¹¹². Although these two SNPs were not in the strong linkage disequilibrium, 61 percent of total variation of CFHR1 was accounted for by rs6677604 without additional variation by rs7517126 when both SNPs were tested together. 78 other SNP-protein associations in the ADNI sample exceeded genome-wide significance (5×10⁻⁸). Our results confirmed previously identified gene-protein associations for interleukin-6 receptor, chemokine CC-4, angiotensin-converting enzyme, and angiotensinogen, although the direction of effect was reversed in some cases. This study is among the first analyses of gene-protein product relationships integrating multiplex-panel proteomics and targeted genes extracted from a GWAS array. With intensive searches taking place for proteomic biomarkers for many diseases, the role of genetic variation takes on new importance and should be considered in interpretation of proteomic results.