Genome-wide association study of biochemical traits in Korcula Island, Croatia

Predicting Biochemical and Physiological Parameters: Deep Learning from IgG Glycome Composition

In immunoglobulin G (IgG), N-glycosylation plays a pivotal role in structure and function. It is often altered in different diseases, suggesting that it could be a promising health biomarker. Studies indicate that IgG glycosylation not only associates with various diseases but also has predictive capabilities. Additionally, changes in IgG glycosylation correlate with physiological and biochemical traits known to reflect overall health state. This study aimed to investigate the power of IgG glycans to predict physiological and biochemical parameters. We developed two models using IgG N-glycan data as an input: a regression model using elastic net and a machine learning model using deep learning. Data were obtained from the Korčula and Vis cohorts. The Korčula cohort data were used to train both models, while the Vis cohort was used exclusively for validation. Our results demonstrated that IgG glycome composition effectively predicts several biochemical and physiological parameters, especially those related to lipid and glucose metabolism and cardiovascular events. Both models performed similarly on the Korčula cohort; however, the deep learning model showed a higher potential for generalization when validated on the Vis cohort. This study reinforces the idea that IgG glycosylation reflects individuals' health state and brings us one step closer to implementing glycan-based diagnostics in personalized medicine. Additionally, it shows that the predictive power of IgG glycans can be used for imputing missing covariate data in deep learning frameworks.

Genetic regulation of post-translational modification of two distinct proteins

Post-translational modifications diversify protein functions and dynamically coordinate their signalling networks, influencing most aspects of cell physiology. Nevertheless, their genetic regulation or influence on complex traits is not fully understood. Here, we compare the genetic regulation of the same PTM of two proteins - glycosylation of transferrin and immunoglobulin G (IgG). By performing genome-wide association analysis of transferrin glycosylation, we identify 10 significantly associated loci, 9 of which were not reported previously. Comparing these with IgG glycosylation-associated genes, we note protein-specific associations with genes encoding glycosylation enzymes (transferrin - MGAT5, ST3GAL4, B3GAT1; IgG - MGAT3, ST6GAL1), as well as shared associations (FUT6, FUT8). Colocalisation analyses of the latter suggest that different causal variants in the FUT genes regulate fucosylation of the two proteins. Glycosylation of these proteins is thus genetically regulated by both shared and protein-specific mechanisms.

An update on the genetics of hyperuricaemia and gout

A central aspect of the pathogenesis of gout is elevated urate concentrations, which lead to the formation of monosodium urate crystals. The clinical features of gout result from an individual's immune response to these deposited crystals. Genome-wide association studies (GWAS) have confirmed the importance of urate excretion in the control of serum urate levels and the risk of gout and have identified the kidneys, the gut and the liver as sites of urate regulation. The genetic contribution to the progression from hyperuricaemia to gout remains relatively poorly understood, although genes encoding proteins that are involved in the NLRP3 (NOD-, LRR- and pyrin domain-containing 3) inflammasome pathway play a part. Genome-wide and targeted sequencing is beginning to identify uncommon population-specific variants that are associated with urate levels and gout. Mendelian randomization studies using urate-associated genetic variants as unconfounded surrogates for lifelong urate exposure have not supported claims that urate is causal for metabolic conditions that are comorbidities of hyperuricaemia and gout. Genetic studies have also identified genetic variants that predict responsiveness to therapies (for example, urate-lowering drugs) for treatment of hyperuricaemia. Future research should focus on large GWAS (that include asymptomatic hyperuricaemic individuals) and on increasing the use of whole-genome sequencing data to identify uncommon genetic variants with increased penetrance that might provide opportunities for clinical translation.

Generalizability and applicability of results obtained from populations of European descent regarding the effect direction and size of HDL-C level-associated genetic variants to the Hungarian general and Roma populations

OBJECTIVES

Large-scale association studies that mainly involve European populations identified many genetic loci related to high-density lipoprotein cholesterol (HDL-C) levels, one of the most important indicators of the risk for cardiovascular diseases. The question with intense speculation of whether the effect estimates obtained from European populations for different HDL-C level-related SNPs are applicable to the Roma ethnicity, the largest minority group in Europe with a South Asian origin, was addressed in the present study.

DESIGN

The associations between 21 SNPs (in the genes LIPC(G), CETP, GALNT2, HMGCP, ABCA1, KCTD10 and WWOX) and HDL-C levels were examined separately in adults of the Hungarian general (N = 1542) and Roma (N = 646) populations by linear regression. Individual effects (direction and size) of single SNPs on HDL-C levels were computed and compared between the study groups and with data published in the literature.

RESULTS

Significant associations between SNPs and HDL-C levels were more frequently found in general subjects than in Roma subjects (11 SNPs in general vs. 4 SNPs in Roma). The CETP gene variants rs1532624, rs708272 and rs7499892 consistently showed significant associations with HDL-C levels across the study groups (p ˂ 0.05), indicating a possible causal variant(s) in this region. Although nominally significant differences in effect size were found for three SNPs (rs693 in gene APOB, rs9989419 in gene CETP, and rs2548861 in gene WWOX) by comparing the general and Roma populations, most of these SNPs did not have a significant effect on HDL-C levels. The β coefficients for SNPs in the Roma population were found to be identical both in direction and magnitude to the effect obtained previously in large-scale studies on European populations.

CONCLUSIONS

The effect of the vast majority of the SNPs on HDL-C levels could be replicated in the Hungarian general and Roma populations, which indicates that the effect size measurements obtained from the literature can be used for risk estimation for both populations.

Genome-wide association analysis identifies multiple loci associated with kidney disease-related traits in Korean populations

Chronic kidney disease (CKD) is an important social health problem characterized by a decrease in the kidney glomerular filtration rate (GFR). In this study, we analyzed genome-wide association studies for kidney disease-related traits using data from a Korean adult health screening cohort comprising 7,064 participants. Kidney disease-related traits analyzed include blood urea nitrogen (BUN), serum creatinine, estimated GFR, and uric acid levels. We detected two genetic loci (SLC14A2 and an intergenic region) and 8 single nucleotide polymorphisms (SNPs) associated with BUN, 3 genetic loci (BCAS3, C17orf82, ALDH2) and 6 SNPs associated with serum creatinine, 3 genetic loci (BCAS3, C17orf82/TBX2, LRP2) and 7 SNPs associated with GFR, and 14 genetic loci (3 in ABCG2/PKD2, 2 in SLC2A9, 3 in intergenic regions on chromosome 4; OTUB1, NRXN2/SLC22A12, CDC42BPG, RPS6KA4, SLC22A9, and MAP4K2 on chromosome 11) and 84 SNPs associated with uric acid levels. By comparing significant genetic loci associated with serum creatinine levels and GFR, rs9895661 in BCAS3 and rs757608 in C17orf82 were simultaneously associated with both traits. The SNPs rs11710227 in intergenic regions on chromosome 3 showing significant association with BUN is newly discovered. Genetic variations of multiple gene loci are associated with kidney disease-related traits, and differences in associations between kidney disease-related traits and genetic variation are dependent on the population. The meanings of the mutations identified in this study will need to be reaffirmed in other population groups in the future.

Replication and fine-mapping of genetic predictors of lipid traits in African-Americans

Circulating lipid concentrations are among the strongest modifiable risk factors for coronary artery disease (CAD). Most genetic studies have focused on Caucasian populations with little information available for populations of African ancestry. Using a cohort of ~2800 African-Americans (AAs) from a biobank at Vanderbilt University (BioVU), we sought to trans-ethnically replicate genetic variants reported by the Global Lipids Genetics Consortium to be associated with lipid traits in Caucasians, followed by fine-mapping those loci using all available variants on the MetaboChip. In AAs, we replicated one of 56 SNPs for total cholesterol (TC) (rs6511720 in LDLR, P=2.15 × 10-8), one of 63 SNPs for high-density lipoprotein cholesterol (HDL-C) (rs3764261 in CETP, P=1.13 × 10-5), two of 46 SNPs for low-density lipoprotein cholesterol (LDL-C) (rs629301 in CELSR2/SORT1, P=1.11 × 10-5 and rs6511720 in LDLR, P=2.47 × 10-5) and one of 34 SNPs for TG (rs645040 in MSL2L1, P=4.29 × 10-4). Using all available variants on MetaboChip for fine mapping, we identified additional variants associated with TC (APOE), HDL-C (LPL and CETP) and LDL-C (APOE). Furthermore, we identified two loci significantly associated with non-HDL-C: APOE/APOC1/TOMM40 and PCSK9. In conclusion, the genetic architecture of lipid traits in AAs differs substantially from that in Caucasians and it remains poorly characterized.

Multivariate discovery and replication of five novel loci associated with Immunoglobulin G N-glycosylation

Joint modeling of a number of phenotypes using multivariate methods has often been neglected in genome-wide association studies and if used, replication has not been sought. Modern omics technologies allow characterization of functional phenomena using a large number of related phenotype measures, which can benefit from such joint analysis. Here, we report a multivariate genome-wide association studies of 23 immunoglobulin G (IgG) N-glycosylation phenotypes. In the discovery cohort, our multi-phenotype method uncovers ten genome-wide significant loci, of which five are novel (IGH, ELL2, HLA-B-C, AZI1, FUT6-FUT3). We convincingly replicate all novel loci via multivariate tests. We show that IgG N-glycosylation loci are strongly enriched for genes expressed in the immune system, in particular antibody-producing cells and B lymphocytes. We empirically demonstrate the efficacy of multivariate methods to discover novel, reproducible pleiotropic effects.Multivariate analysis methods can uncover the relationship between phenotypic measures characterised by modern omic techniques. Here the authors conduct a multivariate GWAS on IgG N-glycosylation phenotypes and identify 5 novel loci enriched in immune system genes.

The KSR2-rs7973260 Polymorphism is Associated with Metabolic Phenotypes, but Not Psychological Phenotypes, in Chinese Elders

OBJECTIVE

To examine the associations between genetic variants of KSR2 (kinase suppressor of RAS)-rs7973260, RAPGEF6 (guanine nucleotide exchange factor 6)-rs3756290, LOC105377703-rs4481363, and subjective well-being (SWB) and depressive symptoms (DSs) in Chinese elders, which were recently associated in a genome-wide association study conducted in Caucasians. The pleiotropic effects of KSR2-rs7973260 on metabolic phenotypes were also explored.

MATERIALS AND METHODS

We used data from 1788 older individuals aged 70-84 years from the aging arm of the Rugao Longevity and Aging Study, a population-based cohort study conducted in the Jiangsu province of China.

RESULTS

No significant distributions of genotype frequencies were observed between life-satisfied and -unsatisfied groups across those with the three polymorphisms. The level of SWB components (positive affect, negative affect, and affect balance) and DSs did not differ among genotypes of the three variants. However, the presence of GA+AA of KSR2-rs7973260 was significantly higher in the metabolic syndrome (MetS), severe hypertriglyceridemia (HTG), and diabetes groups than in control groups (43.7% vs. 37.6%, 46.4% vs. 37.6%, 45.8% vs. 37.9%, respectively). The A allele of rs7973260 was associated with increased risk of MetS, severe HTG, and diabetes with an odds ratios (95% confidence intervals) of 1.289 (1.002-1.658), 1.438 (1.076-1.921), and 1.384 (1.022-1.875), which remained significant after multiple adjustments.

CONCLUSION

Rs7973260, rs3756290, and rs4481363 were not associated with SWB and DSs in Chinese elders. However, the KSR2-rs7973260 A allele exhibited pleiotropic effects on some metabolic phenotypes in Chinese elders. These effects should be validated in future studies.

KIDNEY DISEASE GENETICS AND THE IMPORTANCE OF DIVERSITY IN PRECISION MEDICINE

Kidney disease is a well-known health disparity in the United States where African Americans are affected at higher rates compared with other groups such as European Americans and Mexican Americans. Common genetic variants in the myosin, heavy chain 9, non-muscle (MYH9) gene were initially identified as associated with non-diabetic end-stage renal disease in African Americans, and it is now understood that these variants are in strong linkage disequilibrium with likely causal variants in neighboring APOL1. Subsequent genome-wide and candidate gene studies have suggested that MYH9 common variants among others are also associated with chronic kidney disease and quantitative measures of kidney function in various populations. In a precision medicine setting, it is important to consider genetic effects or genetic associations that differ across racial/ethnic groups in delivering data relevant to disease risk or individual-level patient assessment. Kidney disease and quantitative trait-associated genetic variants have yet to be systematically characterized in multiple racial/ethnic groups. Therefore, to further characterize the prevalence of these genetic variants and their association with kidney related traits, we have genotyped 10 kidney disease or quantitative trait-associated single nucleotide polymorphisms (SNPs) (rs2900976, rs10505955, rs10502868, rs1243400, rs9305354, rs12917707, rs17319721, rs2467853, rs2032487, and rs4821480) in 14,998 participants from the population-based cross-sectional National Health and Nutrition Examination Surveys (NHANES) III and 1999-2002 as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study. In this general adult population ascertained regardless of health status (6,293 non-Hispanic whites, 3,013 non-Hispanic blacks, and 3,542 Mexican Americans), we observed higher rates of chronic kidney disease among non-Hispanic blacks compared with the other groups as expected. We performed single SNP tests of association using linear regressions assuming an additive genetic model adjusted for age, sex, diastolic blood pressure, systolic blood pressure, and type 2 diabetes status for several outcomes including creatinine (urinary), creatinine (serum), albumin (urinary), eGFR, and albumin-to-urinary creatinine ratio (ACR). We also tested for associations between each SNP and chronic kidney disease and albuminuria using logistic regression. Surprisingly, none of the MYH9 variants tested was associated with kidney diseases or traits in non-Hispanic blacks (p>0.05), perhaps attributable to the clinical heterogeneity of kidney disease in this population. Several associations were observed in each racial/ethnic group at p<0.05, but none were consistently associated in the same direction in all three groups. The lack of significant and consistent associations is most likely due to power highlighting the importance of the availability of large, diverse populations for genetic association studies of complex diseases and traits to inform precision medicine efforts in diverse patient populations.

The Relevance of Genomic Signatures at Adhesion GPCR Loci in Humans

Adhesion G protein-coupled receptors (aGPCRs) have a long evolutionary history dating back to very basal unicellular eukaryotes. Almost every vertebrate is equipped with a set of different aGPCRs. Genomic sequence data of several hundred extinct and extant species allows for reconstruction of aGPCR phylogeny in vertebrates and non-vertebrates in general but also provides a detailed view into the recent evolutionary history of human aGPCRs. Mining these sequence sources with bioinformatic tools can unveil many facets of formerly unappreciated aGPCR functions. In this review, we extracted such information from the literature and open public sources and provide insights into the history of aGPCR in humans. This includes comprehensive analyses of signatures of selection, variability of human aGPCR genes, and quantitative traits at human aGPCR loci. As indicated by a large number of genome-wide genotype-phenotype association studies, variations in aGPCR contribute to specific human phenotypes. Our survey demonstrates that aGPCRs are significantly involved in adaptation processes, phenotype variations, and diseases in humans.

Genome-wide association study identifies African-ancestry specific variants for metabolic syndrome

The metabolic syndrome (MetS) is a constellation of metabolic disorders that increase the risk of developing several diseases including type 2 diabetes and cardiovascular diseases. Although genome-wide association studies (GWAS) have successfully identified variants associated with individual traits comprising MetS, the genetic basis and pathophysiological mechanisms underlying the clustering of these traits remain unclear. We conducted GWAS of MetS in 1427 Africans from Ghana and Nigeria followed by replication testing and meta-analysis in another continental African sample from Kenya. Further replication testing was performed in an African American sample from the Atherosclerosis Risk in Communities (ARIC) study. We found two African-ancestry specific variants that were significantly associated with MetS: SNP rs73989312[A] near CA10 that conferred increased risk (P=3.86 × 10(-8), OR=6.80) and SNP rs77244975[C] in CTNNA3 that conferred protection against MetS (P=1.63 × 10(-8), OR=0.15). Given the exclusive expression of CA10 in the brain, our CA10 finding strengthens previously reported link between brain function and MetS. We also identified two variants that are not African specific: rs76822696[A] near RALYL associated with increased MetS risk (P=7.37 × 10(-9), OR=1.59) and rs7964157[T] near KSR2 associated with reduced MetS risk (P=4.52 × 10(-8), Pmeta=7.82 × 10(-9), OR=0.53). The KSR2 locus displayed pleiotropic associations with triglyceride and measures of blood pressure. Rare KSR2 mutations have been reported to be associated with early onset obesity and insulin resistance. Finally, we replicated the LPL and CETP loci previously found to be associated with MetS in Europeans. These findings provide novel insights into the genetics of MetS in Africans and demonstrate the utility of conducting trans-ethnic disease gene mapping studies for testing the cosmopolitan significance of GWAS signals of cardio-metabolic traits.

Homozygous loss-of-function variants in European cosmopolitan and isolate populations

Homozygous loss of function (HLOF) variants provide a valuable window on gene function in humans, as well as an inventory of the human genes that are not essential for survival and reproduction. All humans carry at least a few HLOF variants, but the exact number of inactivated genes that can be tolerated is currently unknown—as are the phenotypic effects of losing function for most human genes. Here, we make use of 1432 whole exome sequences from five European populations to expand the catalogue of known human HLOF mutations; after stringent filtering of variants in our dataset, we identify a total of 173 HLOF mutations, 76 (44%) of which have not been observed previously. We find that population isolates are particularly well suited to surveys of novel HLOF genes because individuals in such populations carry extensive runs of homozygosity, which we show are enriched for novel, rare HLOF variants. Further, we make use of extensive phenotypic data to show that most HLOFs, ascertained in population-based samples, appear to have little detectable effect on the phenotype. On the contrary, we document several genes directly implicated in disease that seem to tolerate HLOF variants. Overall HLOF genes are enriched for olfactory receptor function and are expressed in testes more often than expected, consistent with reduced purifying selection and incipient pseudogenisation.

Rare and low-frequency variants and their association with plasma levels of fibrinogen, FVII, FVIII, and vWF

Fibrinogen, coagulation factor VII (FVII), and factor VIII (FVIII) and its carrier von Willebrand factor (vWF) play key roles in hemostasis. Previously identified common variants explain only a small fraction of the trait heritabilities, and additional variations may be explained by associations with rarer variants with larger effects. The aim of this study was to identify low-frequency (minor allele frequency [MAF] ≥0.01 and <0.05) and rare (MAF <0.01) variants that influence plasma concentrations of these 4 hemostatic factors by meta-analyzing exome chip data from up to 76,000 participants of 4 ancestries. We identified 12 novel associations of low-frequency (n = 2) and rare (n = 10) variants across the fibrinogen, FVII, FVIII, and vWF traits that were independent of previously identified associations. Novel loci were found within previously reported genes and had effect sizes much larger than and independent of previously identified common variants. In addition, associations at KCNT1, HID1, and KATNB1 identified new candidate genes related to hemostasis for follow-up replication and functional genomic analysis. Newly identified low-frequency and rare-variant associations accounted for modest amounts of trait variance and therefore are unlikely to increase predicted trait heritability but provide new information for understanding individual variation in hemostasis pathways.

Analysis of metabolic syndrome components in >15 000 african americans identifies pleiotropic variants: results from the population architecture using genomics and epidemiology study

BACKGROUND

Metabolic syndrome (MetS) refers to the clustering of cardiometabolic risk factors, including dyslipidemia, central adiposity, hypertension, and hyperglycemia, in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS.

METHODS AND RESULTS

Using the Metabochip array in 15 148 African Americans from the Population Architecture using Genomics and Epidemiology (PAGE) study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models that lack power when associations for MetS components are null or have opposite effects, Association-analysis-based-on-subsets uses 1-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With Association-analysis-based-on-subsets, we identify 27 single nucleotide polymorphisms in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, and APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P<2.5e-7, the Bonferroni adjusted P value. Three loci replicate in a Hispanic population, n=5172. A novel African American-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2, and CETP variants, many with opposing effects (eg, the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity).

CONCLUSIONS

We highlight a method to increase power in large-scale genomic association analyses and report a novel variant associated with all MetS components in African Americans. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications.

A general approach for haplotype phasing across the full spectrum of relatedness

Many existing cohorts contain a range of relatedness between genotyped individuals, either by design or by chance. Haplotype estimation in such cohorts is a central step in many downstream analyses. Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations, we have investigated the performance of different phasing methods designed for nominally 'unrelated' individuals. We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods, including those designed specifically for isolated populations. In particular, when large amounts of IBD sharing is present, SHAPEIT2 infers close to perfect haplotypes. Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals. First SHAPEIT2 is run ignoring all explicit family information. We then apply a novel HMM method (duoHMM) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome. This allows the correction of switch errors, detection of recombination events and genotyping errors. We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps, and that it infers far fewer spurious recombination events than Merlin. The method can also detect genotyping errors and infer recombination events in otherwise uninformative families, such as trios and duos. The detected recombination events can be used in association scans for recombination phenotypes. The method provides a simple and unified approach to haplotype estimation, that will be of interest to researchers in the fields of human, animal and plant genetics.

Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or <2(nd) percentile). Follow-up analyses included sequencing of 1,302 additional individuals and genotype-based analysis of 52,221 individuals. We observed significant evidence of association between LDL-C and the burden of rare or low-frequency variants in PNPLA5, encoding a phospholipase-domain-containing protein, and both known and previously unidentified variants in PCSK9, LDLR and APOB, three known lipid-related genes. The effect sizes for the burden of rare variants for each associated gene were substantially higher than those observed for individual SNPs identified from GWASs. We replicated the PNPLA5 signal in an independent large-scale sequencing study of 2,084 individuals. In conclusion, this large whole-exome-sequencing study for LDL-C identified a gene not known to be implicated in LDL-C and provides unique insight into the design and analysis of similar experiments.

Genetics of the first seven proprotein convertase enzymes in health and disease

Members of the substilisin/kexin like proprotein convertase (PCSK) protease family cleave and convert immature pro-proteins into their biologically active forms. By cleaving for example prohormones, cytokines and cell membrane proteins, PCSKs participate in maintaining the homeostasis in a healthy human body. Conversely, erratic enzymatic function is thought to contribute to the pathogenesis of a wide variety of diseases, including obesity and hypercholestrolemia. The first characterized seven PCSK enzymes (PCSK1-2, FURIN, PCSK4-7) process their substrates at a motif made up of paired basic amino acid residues. This feature results in a variable degree of biochemical redundancy in vitro, and consequently, shared substrate molecules between the different PCSK enzymes. This redundancy has confounded our understanding of the specific biological functions of PCSKs. The physiological roles of these enzymes have been best illustrated by the phenotypes of genetically engineered mice and patients that carry mutations in the PCSK genes. Recent developments in genome-wide methodology have generated a large amount of novel information on the genetics of the first seven proprotein convertases. In this review we summarize the reported genetic alterations and their associated phenotypes.

Clinical aspects of urea transporters

Jk antigens, which were identified as urea transporter B (UT-B) in the plasma membrane of erythrocytes, and which determine the Kidd blood type in humans, are involved in transfusion medicine, and even in organ transplantation. The Jk(a-b-) blood type is a consequence of a silent Slc14A1 gene caused by various mutations related to lineage. In addition, the specific mutations related to hypertension and metabolic syndrome cannot be ignored. Genome-wide association studies established Slc14A1 as a related gene of bladder cancer and some genotypes are associated with higher morbidity. This chapter aims to introduce the clinical significance of urea transporters.

Genome-wide association analysis confirms and extends the association of SLC2A9 with serum uric acid levels to Mexican Americans

Increased serum uric acid (SUA) is a risk factor for gout and renal and cardiovascular disease (CVD). The purpose of this study was to identify genetic factors that affect the variation in SUA in 632 Mexican Americans participants of the San Antonio Family Heart Study (SAFHS). A genome-wide association (GWA) analysis was performed using the Illumina Human Hap 550K single nucleotide polymorphism (SNP) microarray. We used a linear regression-based association test under an additive model of allelic effect, while accounting for non-independence among family members via a kinship variance component. All analyses were performed in the software package SOLAR. SNPs rs6832439, rs13131257, and rs737267 in solute carrier protein 2 family, member 9 (SLC2A9) were associated with SUA at genome-wide significance (p < 1.3 × 10⁻⁷). The minor alleles of these SNPs had frequencies of 36.2, 36.2, and 38.2%, respectively, and were associated with decreasing SUA levels. All of these SNPs were located in introns 3–7 of SLC2A9, the location of the previously reported associations in European populations. When analyzed for association with cardiovascular-renal disease risk factors, conditional on SLC2A9 SNPs strongly associated with SUA, significant associations were found for SLC2A9 SNPs with BMI, body weight, and waist circumference (p < 1.4 × 10⁻³) and suggestive associations with albumin-creatinine ratio and total antioxidant status (TAS). The SLC2A9 gene encodes an urate transporter that has considerable influence on variation in SUA. In addition to the primary association locus, suggestive evidence (p < 1.9 × 10⁻⁶) for joint linkage/association (JLA) was found at a previously-reported urate quantitative trait locus (Logarithm of odds score = 3.6) on 3p26.3. In summary, our GWAS extends and confirms the association of SLC2A9 with SUA for the first time in a Mexican American cohort and also shows for the first time its association with cardiovascular-renal disease risk factors.

Gene-centric association signals for haemostasis and thrombosis traits identified with the HumanCVD BeadChip

Coagulation phenotypes show strong intercorrelations, affect cardiovascular disease risk and are influenced by genetic variants. The objective of this study was to search for novel genetic variants influencing the following coagulation phenotypes: factor VII levels, fibrinogen levels, plasma viscosity and platelet count. We genotyped the British Women's Heart and Health Study (n=3,445) and the Whitehall II study (n=5,059) using the Illumina HumanCVD BeadArray to investigate genetic associations and pleiotropy. In addition to previously reported associations (SH2B3, F7/F10, PROCR, GCKR, FGA/FGB/FGG, IL5), we identified novel associations at GRK5 (rs10128498, p=1.30x10(-6)), GCKR (rs1260326, p=1.63x10(-6)), ZNF259-APOA5 (rs651821, p=7.17x10(-6)) with plasma viscosity; and at CSF1 (rs333948, p=8.88x10(-6)) with platelet count. A pleiotropic effect was identified in GCKR which associated with factor VII (p=2.16x10(-7)) and plasma viscosity (p=1.63x10(-6)), and, to a lesser extent, ZNF259-APOA5 which also associated with factor VII and fibrinogen (p<1.00x10-²) and plasma viscosity (p<1.00x10(-5)). Triglyceride associated variants were overrepresented in factor VII and plasma viscosity associations. Adjusting for triglyceride levels resulted in attenuation of associations at the GCKR and ZNF259-APOA5 loci. In addition to confirming previously reported associations, we identified four single nucleotide polymorphisms (SNPs) associated with plasma viscosity and platelet count and found evidence of pleiotropic effects with SNPs in GCKR and ZNF259-APOA5. These triglyceride-associated, pleiotropic SNPs suggest a possible causal role for triglycerides in coagulation.

A non-stop S-antigen gene mutation is associated with late onset hereditary retinal degeneration in dogs

PURPOSE

To identify the causative mutation of canine progressive retinal atrophy (PRA) segregating as an adult onset autosomal recessive disorder in the Basenji breed of dog.

METHODS

Basenji dogs were ascertained for the PRA phenotype by clinical ophthalmoscopic examination. Blood samples from six affected cases and three nonaffected controls were collected, and DNA extraction was used for a genome-wide association study using the canine HD Illumina single nucleotide polymorphism (SNP) array and PLINK. Positional candidate genes identified within the peak association signal region were evaluated.

RESULTS

The highest -Log10(P) value of 4.65 was obtained for 12 single nucleotide polymorphisms on three chromosomes. Homozygosity and linkage disequilibrium analyses favored one chromosome, CFA25, and screening of the S-antigen (SAG) gene identified a non-stop mutation (c.1216T>C), which would result in the addition of 25 amino acids (p.*405Rext*25).

CONCLUSIONS

Identification of this non-stop SAG mutation in dogs affected with retinal degeneration establishes this canine disease as orthologous to Oguchi disease and SAG-associated retinitis pigmentosa in humans, and offers opportunities for genetic therapeutic intervention.

Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers

Glycosylation of immunoglobulin G (IgG) influences IgG effector function by modulating binding to Fc receptors. To identify genetic loci associated with IgG glycosylation, we quantitated N-linked IgG glycans using two approaches. After isolating IgG from human plasma, we performed 77 quantitative measurements of N-glycosylation using ultra-performance liquid chromatography (UPLC) in 2,247 individuals from four European discovery populations. In parallel, we measured IgG N-glycans using MALDI-TOF mass spectrometry (MS) in a replication cohort of 1,848 Europeans. Meta-analysis of genome-wide association study (GWAS) results identified 9 genome-wide significant loci (P<2.27×10⁻⁹) in the discovery analysis and two of the same loci (B4GALT1 and MGAT3) in the replication cohort. Four loci contained genes encoding glycosyltransferases (ST6GAL1, B4GALT1, FUT8, and MGAT3), while the remaining 5 contained genes that have not been previously implicated in protein glycosylation (IKZF1, IL6ST-ANKRD55, ABCF2-SMARCD3, SUV420H1, and SMARCB1-DERL3). However, most of them have been strongly associated with autoimmune and inflammatory conditions (e.g., systemic lupus erythematosus, rheumatoid arthritis, ulcerative colitis, Crohn's disease, diabetes type 1, multiple sclerosis, Graves' disease, celiac disease, nodular sclerosis) and/or haematological cancers (acute lymphoblastic leukaemia, Hodgkin lymphoma, and multiple myeloma). Follow-up functional experiments in haplodeficient Ikzf1 knock-out mice showed the same general pattern of changes in IgG glycosylation as identified in the meta-analysis. As IKZF1 was associated with multiple IgG N-glycan traits, we explored biomarker potential of affected N-glycans in 101 cases with SLE and 183 matched controls and demonstrated substantial discriminative power in a ROC-curve analysis (area under the curve = 0.842). Our study shows that it is possible to identify new loci that control glycosylation of a single plasma protein using GWAS. The results may also provide an explanation for the reported pleiotropy and antagonistic effects of loci involved in autoimmune diseases and haematological cancer.

After analysing glycans attached to human immunoglobulin G in 4,095 individuals, we performed the first genome-wide association study (GWAS) of the glycome of an individual protein. Nine genetic loci were found to associate with glycans with genome-wide significance. Of these, four were enzymes that directly participate in IgG glycosylation, thus the observed associations were biologically founded. The remaining five genetic loci were not previously implicated in protein glycosylation, but the most of them have been reported to be relevant for autoimmune and inflammatory conditions and/or haematological cancers. A particularly interesting gene, IKZF1 was found to be associated with multiple IgG N-glycans. This gene has been implicated in numerous diseases, including systemic lupus erythematosus (SLE). We analysed N-glycans in 101 cases with SLE and 183 matched controls and demonstrated their substantial biomarker potential. Our study shows that it is possible to identify new loci that control glycosylation of a single plasma protein using GWAS. Our results may also provide an explanation for opposite effects of some genes in autoimmune diseases and haematological cancer.

Association of the rs7395662 SNP in the MADD-FOLH1 and several environmental factors with serum lipid levels in the Mulao and Han populations

BACKGROUND

The rs7395662 single nucleotide polymorphism (SNP) in the MADD-FOLH1 has been associated with serum lipid traits, but the results are inconsistent in different populations. The present study was undertaken to investigate the association of rs7395662 SNP and several environmental factors with serum lipid levels in the Guangxi Mulao and Han populations.

METHOD

A total of 721 subjects of Mulao and 727 subjects of Han Chinese were randomly selected from our previous stratified randomized samples. Genotyping of the SNP was performed by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and confirmed by direct sequencing.

RESULTS

Serum apolipoprotein (Apo) B levels were higher in Mulao than in Han (P < 0.01). The allelic and genotypic frequencies in Han were different between males and females (P < 0.05 for each), but there was no difference between Mulao and Han or between Mulao males and females. The levels of low-density lipoprotein cholesterol (LDL-C) and ApoB in Mulao females were different among the genotypes (P < 0.05), the G allele carriers had higher LDL-C and ApoB levels than the G allele non-carriers. The levels of total cholesterol (TC), triglyceride (TG), LDL-C and ApoB in Han males and TC, TG and high-density lipoprotein cholesterol (HDL-C) in Han females were different among the genotypes (P < 0.05-0.01), the subjects with GG genotype in Han males had higher TC, TG, and ApoB and lower LDL-C levels than the subjects with AA or AG genotype, and the G allele carriers in Han females had lower TC and HDL-C levels than the G allele non-carriers. The levels of LDL-C and ApoB in Mulao females were correlated with the genotypes (P < 0.05 for each). The levels of HDL-C and ApoAI in Han males and HDL-C in Han females were correlated with genotypes (P < 0.05-0.001). Serum lipid parameters were also correlated with several environmental factors in both ethnic groups (P < 0.05-0.01).

CONCLUSION

The association of rs7395662 SNP and serum lipid levels is different between the Mulao and Han populations, and between males and females in both ethnic groups.

Polymorphisms in the presumptive promoter region of the SLC2A9 gene are associated with gout in a Chinese male population

Background

Glucose transporter 9 (GLUT9) is a high-capacity/low-affinity urate transporter. To date, several recent genome-wide association studies (GWAS) and follow-up studies have identified genetic variants of SLC2A9 associated with urate concentrations and susceptibility to gout. We therefore investigated associations between gout and polymorphisms and haplotypes in the presumptive promoter region of GLUT9 in Chinese males.

Methodology/Principal Findings

The approximately 2000 bp presumptive promoter region upstream of the start site of exon 1 of GLUT9 was sequenced and subjected to genetic analysis. A genotype-phenotype correlation was performed and polymorphisms-induced changes in transcription factor binding sites were predicted. Of 21 SNPs identified in GLUT9, five had not been previously reported. Two of the SNPs (rs13124007 and rs6850166) were associated with susceptibility to gout (p = 0.009 and p = 0.042, respectively). The C allele of rs13124007 appeared to be the risk allele for predisposition to gout (p = 0.006, OR 1.709 [95% CI 1.162–2.514]). For rs6850166, an increased risk of gout was associated with the A allele (p = 0.029, OR 1.645 [95% CI 1.050–2.577]). After Bonferroni correction, there was statistically difference in rs13124007 allele frequencies between gout cases and controls (P = 0.042). Haplotype analyses showed that haplotype GG was a protective haplotype (p = 0.0053) and haplotype CA was associated with increased risk of gout (p = 0.0326). Genotype-phenotype analysis among gout patients revealed an association of rs13124007 with serum triglycerides levels (P = 0.001). The C to G substitution in polymorphism rs13124007 resulted in a loss of a binding site for transcription factor interferon regulatory factor 1 (IRF-1).

Conclusions/Significance

Polymorphisms rs13124007 and rs6850166 are associated with susceptibility to gout in Chinese males.

Association of medication with the human plasma N-glycome

Glycosylation is highly variable depending on many environmental factors. Using our fully quantitative high-throughput normal phase hydrophilic interaction liquid chromatography platform we have identified glycosylation changes associated with medication in the plasma N-glycome from three different population cohorts: ORCADES from the Orkney Islands in Scotland and CROATIA-Vis and CROATIA-Korcula from the Croatian islands of Vis and Korcula. Associations between glycosylation and the use of hormones (oral contraceptives, hormone replacement therapy), nonsteroidal anti-inflammatory drugs (aspirin and other NSAIDs), oral steroids (prednisolone) and steroid inhalers (beclomethasone) were investigated. Significant differences associated with usage of oral contraceptives were found with increased core-fucosylated biantennary glycans. Decreases in core-fucosylated biantennary glycans, core-fucosylated triantennary glycans with outer-arm fucose, and high mannosylated glycans were associated with the use of anti-inflammatory drugs. All of the changes in glycosylation were independent of blood group status. In conclusion, hormones and anti-inflammatory medication were associated with changes in glycosylation, possibly as a result of the modulatory effect of these drugs on the inflammatory response. In general, cancer is associated with inflammation, and many glycoproteins in the plasma are acute phase related to the host response. These preliminary data indicate the importance of correcting the levels of glycans used as biomarkers for the effects of medication.

Single nucleotide polymorphism in gene encoding transcription factor Prep1 is associated with HIV-1-associated dementia

Background

Infection with HIV-1 may result in severe cognitive and motor impairment, referred to as HIV-1-associated dementia (HAD). While its prevalence has dropped significantly in the era of combination antiretroviral therapy, milder neurocognitive disorders persist with a high prevalence. To identify additional therapeutic targets for treating HIV-associated neurocognitive disorders, several candidate gene polymorphisms have been evaluated, but few have been replicated across multiple studies.

Methods

We here tested 7 candidate gene polymorphisms for association with HAD in a case-control study consisting of 86 HAD cases and 246 non-HAD AIDS patients as controls. Since infected monocytes and macrophages are thought to play an important role in the infection of the brain, 5 recently identified single nucleotide polymorphisms (SNPs) affecting HIV-1 replication in macrophages in vitro were also tested.

Results

The CCR5 wt/Δ32 genotype was only associated with HAD in individuals who developed AIDS prior to 1991, in agreement with the observed fading effect of this genotype on viral load set point. A significant difference in genotype distribution among all cases and controls irrespective of year of AIDS diagnosis was found only for a SNP in candidate gene PREP1 (p = 1.2×10⁻⁵). Prep1 has recently been identified as a transcription factor preferentially binding the −2,518 G allele in the promoter of the gene encoding MCP-1, a protein with a well established role in the etiology of HAD.

Conclusion

These results support previous findings suggesting an important role for MCP-1 in the onset of HIV-1-associated neurocognitive disorders.

Genome-wide association of serum uric acid concentration: replication of sequence variants in an island population of the Adriatic coast of Croatia

A genome-wide association study of serum uric acid (SUA) laevels was performed in a relatively isolated population of European descent from an island of the Adriatic coast of Croatia. The study sample included 532 unrelated and 768 related individuals from 235 pedigrees. Inflation due to relatedness was controlled by using genomic control. Genetic association was assessed with 2,241,249 single nucleotide polymorphisms (SNPs) in 1300 samples after adjusting for age and gender. Our study replicated four previously reported SUA loci (SLC2A9, ABCG2, RREB1, and SLC22A12). The strongest association was found with a SNP in SLC2A9 (rs13129697, P=2.33×10(-19)), which exhibited significant gender-specific effects, 35.76 μmol/L (P=2.11×10(-19)) in females and 19.58 μmol/L (P=5.40×10(-5)) in males. Within this region of high linkage disequilibrium, we also detected a strong association with a nonsynonymous SNP, rs16890979 (P=2.24×10(-17)), a putative causal variant for SUA variation. In addition, we identified several novel loci suggestive of association with uric acid levels (SEMA5A, TMEM18, SLC28A2, and ODZ2), although the P-values (P<5×10(-6)) did not reach the threshold of genome-wide significance. Together, these findings provide further confirmation of previously reported uric-acid-related genetic variants and highlight suggestive new loci for additional investigation.

Profound obesity secondary to hyperphagia in mice lacking kinase suppressor of ras 2

The kinase suppressor of ras 2 (KSR2) gene resides at human chromosome 12q24, a region linked to obesity and type 2 diabetes (T2D). While knocking out and phenotypically screening mouse orthologs of thousands of druggable human genes, we found KSR2 knockout (KSR2(-/-)) mice to be more obese and glucose intolerant than melanocortin 4 receptor(-/-) (MC4R(-/-)) mice. The obesity and T2D of KSR2(-/-) mice resulted from hyperphagia which was unresponsive to leptin and did not originate downstream of MC4R. The kinases AMP-activated protein kinase (AMPK) and mammalian target of rapamycin (mTOR) are each linked to food intake regulation, but only mTOR had increased activity in KSR2(-/-) mouse brain, and the ability of rapamycin to inhibit food intake in KSR2(-/-) mice further implicated mTOR in this process. The metabolic phenotype of KSR2 heterozygous (KSR2(+/minus;)) and KSR2(-/-) mice suggests that human KSR2 variants may contribute to a similar phenotype linked to human chromosome 12q24.

CUBN is a gene locus for albuminuria

Identification of genetic risk factors for albuminuria may alter strategies for early prevention of CKD progression, particularly among patients with diabetes. Little is known about the influence of common genetic variants on albuminuria in both general and diabetic populations. We performed a meta-analysis of data from 63,153 individuals of European ancestry with genotype information from genome-wide association studies (CKDGen Consortium) and from a large candidate gene study (CARe Consortium) to identify susceptibility loci for the quantitative trait urinary albumin-to-creatinine ratio (UACR) and the clinical diagnosis microalbuminuria. We identified an association between a missense variant (I2984V) in the CUBN gene, which encodes cubilin, and both UACR (P = 1.1 × 10(-11)) and microalbuminuria (P = 0.001). We observed similar associations among 6981 African Americans in the CARe Consortium. The associations between this variant and both UACR and microalbuminuria were significant in individuals of European ancestry regardless of diabetes status. Finally, this variant associated with a 41% increased risk for the development of persistent microalbuminuria during 20 years of follow-up among 1304 participants with type 1 diabetes in the prospective DCCT/EDIC Study. In summary, we identified a missense CUBN variant that associates with levels of albuminuria in both the general population and in individuals with diabetes.

A genome-wide association study of serum uric acid in African Americans

Background

Uric acid is the primary byproduct of purine metabolism. Hyperuricemia is associated with body mass index (BMI), sex, and multiple complex diseases including gout, hypertension (HTN), renal disease, and type 2 diabetes (T2D). Multiple genome-wide association studies (GWAS) in individuals of European ancestry (EA) have reported associations between serum uric acid levels (SUAL) and specific genomic loci. The purposes of this study were: 1) to replicate major signals reported in EA populations; and 2) to use the weak LD pattern in African ancestry population to better localize (fine-map) reported loci and 3) to explore the identification of novel findings cognizant of the moderate sample size.

Methods

African American (AA) participants (n = 1,017) from the Howard University Family Study were included in this study. Genotyping was performed using the Affymetrix^® Genome-wide Human SNP Array 6.0. Imputation was performed using MACH and the HapMap reference panels for CEU and YRI. A total of 2,400,542 single nucleotide polymorphisms (SNPs) were assessed for association with serum uric acid under the additive genetic model with adjustment for age, sex, BMI, glomerular filtration rate, HTN, T2D, and the top two principal components identified in the assessment of admixture and population stratification.

Results

Four variants in the gene SLC2A9 achieved genome-wide significance for association with SUAL (p-values ranging from 8.88 × 10^-9 to 1.38 × 10^-9). Fine-mapping of the SLC2A9 signals identified a 263 kb interval of linkage disequilibrium in the HapMap CEU sample. This interval was reduced to 37 kb in our AA and the HapMap YRI samples.

Conclusions

The most strongly associated locus for SUAL in EA populations was also the most strongly associated locus in this AA sample. This finding provides evidence for the role of SLC2A9 in uric acid metabolism across human populations. Additionally, our findings demonstrate the utility of following-up EA populations GWAS signals in African-ancestry populations with weaker linkage disequilibrium.

The genetics of obesity and the metabolic syndrome

In this review, we discuss the genetic architecture of obesity and the metabolic syndrome, highlighting recent advances in identifying genetic variants and loci responsible for a portion of the variation in components of the metabolic syndrome, namely, adiposity traits, serum HDL and triglycerides, blood pressure, and glycemic traits. We focus particularly on recent progress from large-scale genome-wide association studies (GWAS), by detailing their successes and how lessons learned can pave the way for future discovery. Results from recent GWAS coalesce with earlier work suggesting numerous interconnections between obesity and the metabolic syndrome, developed through several potentially pleiotropic effects. We detail recent work by way of a case study on the cadherin 13 gene and its relation with adiponectin in the HyperGEN and the Framingham Heart Studies, and its association with obesity and the metabolic syndrome. We provide also a gene network analysis of recent variants related to obesity and metabolic syndrome discovered through genome-wide association studies, and 4 gene networks based on searching the NCBI database.

Gene-based interaction analysis by incorporating external linkage disequilibrium information

Gene-gene interactions have an important role in complex human diseases. Detection of gene-gene interactions has long been a challenge due to their complexity. The standard method aiming at detecting SNP-SNP interactions may be inadequate as it does not model linkage disequilibrium (LD) among SNPs in each gene and may lose power due to a large number of comparisons. To improve power, we propose a principal component (PC)-based framework for gene-based interaction analysis. We analytically derive the optimal weight for both quantitative and binary traits based on pairwise LD information. We then use PCs to summarize the information in each gene and test for interactions between the PCs. We further extend this gene-based interaction analysis procedure to allow the use of imputation dosage scores obtained from a popular imputation software package, MACH, which incorporates multilocus LD information. To evaluate the performance of the gene-based interaction tests, we conducted extensive simulations under various settings. We demonstrate that gene-based interaction tests are more powerful than SNP-based tests when more than two variants interact with each other; moreover, tests that incorporate external LD information are generally more powerful than those that use genotyped markers only. We also apply the proposed gene-based interaction tests to a candidate gene study on high-density lipoprotein. As our method operates at the gene level, it can be applied to a genome-wide association setting and used as a screening tool to detect gene-gene interactions.

Interactions between genetic variants in glucose transporter type 9 (SLC2A9) and dietary habits in serum uric acid regulation

AIM

To investigate possible interactions between genetic variants in glucose transporter type 9 (SLC2A9) gene and dietary habits in serum uric acid regulation.

METHODS

Participants for this study were recruited from two isolated Croatian island communities of Vis (n=918) and Korcula (n=898). Three single nucleotide polymorphisms (SNP) from the SLC2A9 gene (rs1014290, rs6449213, rs737267) were correlated with dietary habits and uric acid.

RESULTS

A significant decrease in uric acid levels was recorded with increasing consumption of milk, sour cream, duck and turkey, and eggs. The only significant interaction was found between potato consumption and rs737267 and a near-significant interaction was found between soft drinks and rs1014290 (interaction P=0.068). Increased consumption of soft drinks interacting with the TT genotype at rs1014290 increased serum uric acid. No significant interactions were observed between food products consumption and rs6449213.

CONCLUSION

There is a certain extent of interaction between SLC2A9 and dietary patterns in serum uric acid determination. The metabolic effect of soft drinks seems to be determined by the underlying genotype of rs1014290.

Predictive value of 8 genetic loci for serum uric acid concentration

AIM

To investigate the value of genomic information in prediction of individual serum uric acid concentrations.

METHODS

Three population samples were investigated: from isolated Adriatic island communities of Vis (n=980) and Korcula (n=944), and from general population of the city of Split (n=507). Serum uric acid concentration was correlated with the genetic risk score based on 8 previously described genes: PDZK1, GCKR, SLC2A9, ABCG2, LRRC16A, SLC17A1, SLC16A9, and SLC22A12, represented by a total of 16 single-nucleotide polymorphisms (SNP). The data were analyzed using classification and regression tree (CART) and general linear modeling.

RESULTS

The most important variables for uric acid prediction with CART were genetic risk score in men and age in women. The percent of variance for any single SNP in predicting serum uric acid concentration varied from 0.0%-2.0%. The use of genetic risk score explained 0.1%-2.5% of uric acid variance in men and 3.9%-4.9% in women. The highest percent of variance was obtained when age, sex, and genetic risk score were used as predictors, with a total of 30.9% of variance in pooled analysis.

CONCLUSION

Despite overall low percent of explained variance, uric acid seems to be among the most predictive human quantitative traits based on the currently available SNP information. The use of genetic risk scores is a valuable approach in genetic epidemiology and increases the predictability of human quantitative traits based on genomic information compared with single SNP approach.

Meta-analysis and imputation refines the association of 15q25 with smoking quantity

Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

Gene expression levels as endophenotypes in genome-wide association studies of Alzheimer disease

BACKGROUND

Late-onset Alzheimer disease (LOAD) is a common disorder with a substantial genetic component. We postulate that many disease susceptibility variants act by altering gene expression levels.

METHODS

We measured messenger RNA (mRNA) expression levels of 12 LOAD candidate genes in the cerebella of 200 subjects with LOAD. Using the genotypes from our LOAD genome-wide association study for the cis-single nucleotide polymorphisms (SNPs) (n = 619) of these 12 LOAD candidate genes, we tested for associations with expression levels as endophenotypes. The strongest expression cis-SNP was tested for AD association in 7 independent case-control series (2,280 AD and 2,396 controls).

RESULTS

We identified 3 SNPs that associated significantly with IDE (insulin degrading enzyme) expression levels. A single copy of the minor allele for each significant SNP was associated with approximately twofold higher IDE expression levels. The most significant SNP, rs7910977, is 4.2 kb beyond the 3' end of IDE. The association observed with this SNP was significant even at the genome-wide level (p = 2.7 x 10(-8)). Furthermore, the minor allele of rs7910977 associated significantly (p = 0.0046) with reduced LOAD risk (OR = 0.81 with a 95% CI of 0.70-0.94), as expected biologically from its association with elevated IDE expression.

CONCLUSIONS

These results provide strong evidence that IDE is a late-onset Alzheimer disease (LOAD) gene with variants that modify risk of LOAD by influencing IDE expression. They also suggest that the use of expression levels as endophenotypes in genome-wide association studies may provide a powerful approach for the identification of disease susceptibility alleles.

Concordant association of insulin degrading enzyme gene (IDE) variants with IDE mRNA, Abeta, and Alzheimer's disease

Background

The insulin-degrading enzyme gene (IDE) is a strong functional and positional candidate for late onset Alzheimer's disease (LOAD).

Methodology/Principal Findings

We examined conserved regions of IDE and its 10 kb flanks in 269 AD cases and 252 controls thereby identifying 17 putative functional polymorphisms. These variants formed eleven haplotypes that were tagged with ten variants. Four of these showed significant association with IDE transcript levels in samples from 194 LOAD cerebella. The strongest, rs6583817, which has not previously been reported, showed unequivocal association (p = 1.5×10⁻⁸, fold-increase = 2.12,); the eleven haplotypes were also significantly associated with transcript levels (global p = 0.003). Using an in vitro dual luciferase reporter assay, we found that rs6583817 increases reporter gene expression in Be(2)-C (p = 0.006) and HepG2 (p = 0.02) cell lines. Furthermore, using data from a recent genome-wide association study of two Croatian isolated populations (n = 1,879), we identified a proxy for rs6583817 that associated significantly with decreased plasma Aβ40 levels (ß = −0.124, p = 0.011) and total measured plasma Aβ levels (b = −0.130, p = 0.009). Finally, rs6583817 was associated with decreased risk of LOAD in 3,891 AD cases and 3,605 controls. (OR = 0.87, p = 0.03), and the eleven IDE haplotypes (global p = 0.02) also showed significant association.

Conclusions

Thus, a previously unreported variant unequivocally associated with increased IDE expression was also associated with reduced plasma Aß40 and decreased LOAD susceptibility. Genetic association between LOAD and IDE has been difficult to replicate. Our findings suggest that targeted testing of expression SNPs (eSNPs) strongly associated with altered transcript levels in autopsy brain samples may be a powerful way to identify genetic associations with LOAD that would otherwise be difficult to detect.

What lies behind serum urate concentration? Insights from genetic and genomic studies

Many factors, including genetic components and acquired factors such as obesity and alcohol consumption, influence serum uric acid (urate) concentrations. Since serum urate concentrations are determined by the balance between renal urate excretion and the volume of urate produced via purine metabolism, urate transporter genes as well as genes coding for enzymes involved in purine metabolism affect serum urate concentrations. URAT1 was the first transporter affecting serum urate concentrations to be identified. Using the characterization of this transporter as an indicator, several transporters have been shown to transport urate, allowing the construction of a synoptic renal urate transport model. Notable re-absorptive urate transporters are URAT1 at apical membranes and GLUT9 at basolateral membranes, while ABCG2, MRP4 (multidrug resistance protein 4) and NPT1 are secretive transporters at apical membranes. Recent genome-wide association studies have led to validation of the in vitro model constructed from each functional analysis of urate transporters, and identification of novel candidate genes related to urate metabolism and transport proteins, such as glucokinase regulatory protein (GKRP), PDZK1 and MCT9. However, the function and physiologic roles of several candidates, as well as the influence of acquired factors such as obesity, foods, or alcoholic beverages, remain unclear.