We conducted a systematic study of top susceptibility variants from a genome-wide association (GWA) study of bipolar disorder to gain insight into the functional consequences of genetic variation ...influencing disease risk. We report here the results of experiments to explore the effects of these susceptibility variants on DNA methylation and mRNA expression in human cerebellum samples. Among the top susceptibility variants, we identified an enrichment of cis regulatory loci on mRNA expression (eQTLs), and a significant excess of quantitative trait loci for DNA CpG methylation, hereafter referred to as methylation quantitative trait loci (mQTLs). Bipolar disorder susceptibility variants that cis regulate both cerebellar expression and methylation of the same gene are a very small proportion of bipolar disorder susceptibility variants. This finding suggests that mQTLs and eQTLs provide orthogonal ways of functionally annotating genetic variation within the context of studies of pathophysiology in brain. No lymphocyte mQTL enrichment was found, suggesting that mQTL enrichment was specific to the cerebellum, in contrast to eQTLs. Separately, we found that using mQTL information to restrict the number of single-nucleotide polymorphisms studied enhances our ability to detect a significant association. With this restriction a priori informed by the observed functional enrichment, we identified a significant association (rs12618769, P(bonferroni)<0.05) from two other GWA studies (TGen+GAIN; 2191 cases and 1434 controls) of bipolar disorder, which we replicated in an independent GWA study (WTCCC). Collectively, our findings highlight the importance of integrating functional annotation of genetic variants for gene expression and DNA methylation to advance the biological understanding of bipolar disorder.
Aims/hypothesis
We conducted genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) analyses to identify and characterise risk loci for type 2 diabetes in ...Mexican-Americans from Starr County, TX, USA.
Method
Using 1.8 million directly interrogated and imputed genotypes in 837 unrelated type 2 diabetes cases and 436 normoglycaemic controls, we conducted Armitage trend tests. To improve power in this population with high disease rates, we also performed ordinal regression including an intermediate class with impaired fasting glucose and/or glucose tolerance. These analyses were followed by meta-analysis with a study of 967 type 2 diabetes cases and 343 normoglycaemic controls from Mexico City, Mexico.
Result
The top signals (unadjusted
p
value <1 × 10
−5
) included 49 single nucleotide polymorphisms (SNPs) in eight gene regions (
PER3
,
PARD3B
,
EPHA4
,
TOMM7
,
PTPRD
,
HNT
also known as
RREB1
,
LOC729993
and
IL34
) and six intergenic regions. Among these was a missense polymorphism (rs10462020; Gly639Val) in the clock gene
PER3
, a system recently implicated in diabetes. We also report a second signal (minimum
p
value 1.52 × 10
−6
) within
PTPRD
, independent of the previously implicated SNP, in a population of Han Chinese. Top meta-analysis signals included known regions
HNF1A
and
KCNQ1
. Annotation of top association signals in both studies revealed a marked excess of
trans
-acting eQTL in both adipose and muscle tissues.
Conclusions/Interpretation
In the largest study of type 2 diabetes in Mexican populations to date, we identified modest associations of novel and previously reported SNPs. In addition, in our top signals we report significant excess of SNPs that predict transcript levels in muscle and adipose tissues.
Using a derivation cohort (N=349), we developed the first warfarin dosing algorithm that includes recently discovered polymorphisms in VKORC1 and CYP2C9 associated with warfarin dose requirement in ...African Americans (AAs). We tested our novel algorithm in an independent cohort of 129 AAs and compared the dose prediction to the International Warfarin Pharmacogenetics Consortium (IWPC) dosing algorithms. Our algorithm explains more of the phenotypic variation (R(2)=0.27) than the IWPC pharmacogenomics (R(2)=0.15) or clinical (R(2)=0.16) algorithms. Among high-dose patients, our algorithm predicted a higher proportion of patients within 20% of stable warfarin dose (45% vs 29% and 2% in the IWPC pharmacogenomics and clinical algorithms, respectively). In contrast to our novel algorithm, a significant inverse correlation between predicted dose and percent West African ancestry was observed for the IWPC pharmacogenomics algorithm among patients requiring ⩾60 mg per week (β=-2.04, P=0.02).
The use of cell‐based models has emerged as a promising means to discover and validate pharmacologic phenotype–genotype relationships. The availability of large‐scale genome studies in both human and ...model systems is now allowing us an unprecedented opportunity to understand how well cell‐based models identify clinically relevant genetic variants associated with drug response and toxicity. Here we review these studies and the emerging translational information.
Clinical Pharmacology & Therapeutics (2012); 92 4, 425–427. doi:10.1038/clpt.2012.115
Platinating agents are used in the treatment of many cancers, yet they can induce toxicities and resistance that limit their utility. Using previously published and additional world population panels ...of diverse ancestry totaling 608 lymphoblastoid cell lines (LCLs), we performed meta-analyses of over 3 million single-nucleotide polymorphisms (SNPs) for both carboplatin- and cisplatin-induced cytotoxicity. The most significant SNP in the carboplatin meta-analysis is located in an intron of NBAS (neuroblastoma amplified sequence; P=5.1 × 10(-7)). The most significant SNP in the cisplatin meta-analysis is upstream of KRT16P2 (P=5.8 × 10(-7)). We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Most of the variants that associate with platinum-induced cytotoxicity are polymorphic across multiple world populations; therefore, they could be tested in follow-up studies in diverse clinical populations. Seven genes previously implicated in platinating agent response, including BCL2 (B-cell CLL/lymphoma 2), GSTM1 (glutathione S-transferase mu 1), GSTT1, ERCC2 and ERCC6, were also implicated in our meta-analyses.
Variation in the expression level and activity of genes involved in drug disposition and action ('pharmacogenes') can affect drug response and toxicity, especially when in tissues of pharmacological ...importance. Previous studies have relied primarily on microarrays to understand gene expression differences, or have focused on a single tissue or small number of samples. The goal of this study was to use RNA-sequencing (RNA-seq) to determine the expression levels and alternative splicing of 389 Pharmacogenomics Research Network pharmacogenes across four tissues (liver, kidney, heart and adipose) and lymphoblastoid cell lines, which are used widely in pharmacogenomics studies. Analysis of RNA-seq data from 139 different individuals across the 5 tissues (20-45 individuals per tissue type) revealed substantial variation in both expression levels and splicing across samples and tissue types. Comparison with GTEx data yielded a consistent picture. This in-depth exploration also revealed 183 splicing events in pharmacogenes that were previously not annotated. Overall, this study serves as a rich resource for the research community to inform biomarker and drug discovery and use.
To compare three groupings of Electronic Health Record (EHR) billing codes for their ability to represent clinically meaningful phenotypes and to replicate known genetic associations. The three ...tested coding systems were the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, the Agency for Healthcare Research and Quality Clinical Classification Software for ICD-9-CM (CCS), and manually curated "phecodes" designed to facilitate phenome-wide association studies (PheWAS) in EHRs.
We selected 100 disease phenotypes and compared the ability of each coding system to accurately represent them without performing additional groupings. The 100 phenotypes included 25 randomly-chosen clinical phenotypes pursued in prior genome-wide association studies (GWAS) and another 75 common disease phenotypes mentioned across free-text problem lists from 189,289 individuals. We then evaluated the performance of each coding system to replicate known associations for 440 SNP-phenotype pairs.
Out of the 100 tested clinical phenotypes, phecodes exactly matched 83, compared to 53 for ICD-9-CM and 32 for CCS. ICD-9-CM codes were typically too detailed (requiring custom groupings) while CCS codes were often not granular enough. Among 440 tested known SNP-phenotype associations, use of phecodes replicated 153 SNP-phenotype pairs compared to 143 for ICD-9-CM and 139 for CCS. Phecodes also generally produced stronger odds ratios and lower p-values for known associations than ICD-9-CM and CCS. Finally, evaluation of several SNPs via PheWAS identified novel potential signals, some seen in only using the phecode approach. Among them, rs7318369 in PEPD was associated with gastrointestinal hemorrhage.
Our results suggest that the phecode groupings better align with clinical diseases mentioned in clinical practice or for genomic studies. ICD-9-CM, CCS, and phecode groupings all worked for PheWAS-type studies, though the phecode groupings produced superior results.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Genome-wide association studies (GWAS) have identified thousands of variants robustly associated with complex traits. However, the biological mechanisms underlying these associations are, in general, ...not well understood. We propose a gene-based association method called PrediXcan that directly tests the molecular mechanisms through which genetic variation affects phenotype. The approach estimates the component of gene expression determined by an individual's genetic profile and correlates 'imputed' gene expression with the phenotype under investigation to identify genes involved in the etiology of the phenotype. Genetically regulated gene expression is estimated using whole-genome tissue-dependent prediction models trained with reference transcriptome data sets. PrediXcan enjoys the benefits of gene-based approaches such as reduced multiple-testing burden and a principled approach to the design of follow-up experiments. Our results demonstrate that PrediXcan can detect known and new genes associated with disease traits and provide insights into the mechanism of these associations.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SBMB, UILJ, UKNU, UL, UM, UPUK
Population divergence impacts the degree of population stratification in Genome Wide Association Studies. We aim to: (i) investigate type-I error rate as a function of population divergence (F
ST
) ...in multi-ethnic (admixed) populations; (ii) evaluate the statistical power and effect size estimates; and (iii) investigate the impact of population stratification on the results of gene-based analyses. Quantitative phenotypes were simulated. Type-I error rate was investigated for Single Nucleotide Polymorphisms (SNPs) with varying levels of F
ST
between the ancestral European and African populations. Type-II error rate was investigated for a SNP characterized by a high value of F
ST
. In all tests, genomic MDS components were included to correct for population stratification. Type-I and type-II error rate was adequately controlled in a population that included two distinct ethnic populations but not in admixed samples. Statistical power was reduced in the admixed samples. Gene-based tests showed no residual inflation in type-I error rate.
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