Genome-wide Association Studies In Cohorts Research Articles

Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden

Lithium is the most effective treatment for bipolar disorder, resulting in strong suicide prevention effects. The therapeutic range of lithium, however, is narrow and treatment initiation requires individual titration to address inter-individual variability. We aimed to improve lithium dose prediction using clinical and genomic data. We performed a population pharmacokinetic study followed by a genome-wide association study (GWAS), including two clinical Swedish cohorts. Participants in cohort 1 were from specialised outpatient clinics at Huddinge Hospital, in Stockholm, Sweden, and participants in cohort 2 were identified using the Swedish National Quality Registry for Bipolar disorder (BipoläR). Patients who received a lithium dose corresponding to at least one tablet of lithium sulphate (6 mmol) per day and had clinically relevant plasma concentrations of lithium were included in the study. Data on age, sex, bodyweight, height, creatinine concentration, estimated glomerular filtration rate (eGFR), lithium preparation, number of tablets of lithium per day, serum lithium concentration, and medications affecting kidney function (C09 antihypertensives, C03 [except C03D] sodium-retaining diuretics, and non-steroidal anti-inflammatory drugs) were obtained retrospectively for several timepoints when possible from electronic health records, BipoläR, and the Swedish prescription registry. The median time between timepoints was 1·07 years for cohort 1 and 1·09 years for cohort 2. The primary outcome of interest was the natural logarithm of total body clearance for lithium (CLLi) associated with the clinical variables. The residual effects after accounting for age and sex, representing the individual-level effects (CLLi,age/sex), were used as the dependent variable in a GWAS. 2357 patients who were administered lithium (1423 women [60·4%] and 934 men [39·6%]; mean age 53·6 years [range 17-89], mainly of European descent) were included and 5627 data points were obtained. Age (variance explained [R2]: R2cohort1=0·41 and R2cohort2=0·31; both p<0·0001), sex (R2cohort1=0·0063 [p=0·045] and R2cohort2=0·026 [p<0·0001]), eGFR (R2cohort1=0·38 and R2cohort2=0·20; both p<0·0001), comedication with diuretics (R2cohort1=0·0058 [p=0·014] and R2cohort2=0·0026 [p<0·0001]), and agents acting on the renin-aldosterone-angiotensin system (R2cohort1=0·028 and R2cohort2=0·015; both p<0·0001) were clinical predictors of CLLi. Notably, an association between CLLi and serum lithium was observed, with a lower CLLi being associated with higher serum lithium (R2cohort1=0·13 and R2cohort2=0·15; both p<0·0001). In a GWAS of CLLi,age/sex, one locus was associated with a change in CLLi (rs583503; β=-0·053 [95% CI -0·071 to -0·034]; p<0·00000005). We also found enrichment of the associations with genes expressed in the medulla (p=0·0014, corrected FDR=0·04) and cortex of the kidney (p=0·0015, corrected FDR=0·04), as well as associations with polygenic risk scores for eGFR (p value threshold: 0·05, p=0·01), body-mass index (p value threshold: 0·05, p=0·00025), and blood urea nitrogen (p value threshold: 0·001, p=0·00043). The model based on six clinical predictors explained 61·4% of the variance in CLLi in cohort 1 and 49·8% in cohort 2. Adding genetic markers did not lead to major improvement of the models: within the subsample of genotyped individuals, the variance explained only increased from 59·32% to 59·36% in cohort 1 and from 49·21% to 50·03% in cohort 2 when including rs583503 and the four first principal components. Our model predictors could be used clinically to better guide lithium dosage, shortening the time to reach therapeutic concentrations, thus improving care. Identification of the first genomic locus and PRS to be associated with CLLi introduces the opportunity of individualised medicine in lithium treatment. Stanley Medical Research Institute, Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Swedish Research Council, Söderström-Königska Foundation, Bror Gadelius Minnesfond, Swedish Mental Health Fund, Karolinska Institutet and Hospital.

Variants and expression changes in PPAR-encoding genes display no significant association with schizophrenia.

A few studies suggested the contribution of PPARs to the etiology of schizophrenia (SCZ). However, it is still not clear whether variants in PPAR-encoding genes have a direct association with SCZ. The potential linkage between SCZ and the variants within PPAR encoding genes (PPARA, PPARD, and PPARG) was tested in a large cohort genome-wide association study (GWAS). Then, a mega-analysis was conducted using 14 gene expression profiling experiments in various human brain regions. Finally, the expression levels of the three PPAR-encoding genes were quantified in early-onset SCZ patients. Only one PPARG polymorphisms, rs62242085, presented a minor frequency deviation in the SCZ cohort (P-value = 0.035). None of the PPAR-encoding genes presented significant expression change within the brain regions profiled in 14 datasets acquired from different populations (P-value > 0.14) or in the whole blood of early-onset overall SCZ patients (P-value > 0.22). However, compared with healthy female controls, female early-onset SCZ patients presented a moderate but significant decrease in the expression level of PPARD (LFC = −0.55; P-value = 0.02) and a strong, but non-significant decrease in expression of PPARG (LFC = −1.30; P-value = 0.13). Our results do not support a significant association between variants in PPAR-encoding genes and SCZ, but suggest a necessity to explore the role of PPARD and PPARG in early SCZ phenotypes, specifically in females.

The impact of disregarding family structure on genome-wide association analysis of complex diseases in cohorts with simple pedigrees.

The generalized linear mixed models (GLMMs) methodology is the standard framework for genome-wide association studies (GWAS) of complex diseases in family-based cohorts. Fitting GLMMs in very large cohorts, however, can be computationally demanding. Also, the modified versions of GLMM using faster algorithms may underperform, for instance when a single nucleotide polymorphism (SNP) is correlated with fixed-effects covariates. We investigated the extent to which disregarding family structure may compromise GWAS in cohorts with simple pedigrees by contrasting logistic regression models (i.e., with no family structure) to three LMMs-based ones. Our analyses showed that the logistic regression models in general resulted in smaller P values compared with the LMMs-based models; however, the differences in P values were mostly minor. Disregarding family structure had little impact on determining disease-associated SNPs at genome-wide level of significance (i.e., P < 5E-08) as the four P values resulted from the tested methods for any SNP were all below or all above 5E-08. Nevertheless, larger discrepancies were detected between logistic regression and LMMs-based models at suggestive level of significance (i.e., of 5E-08 ≤ P < 5E-06). The SNP effects estimated by the logistic regression models were not statistically different from those estimated by GLMMs that implemented Wald's test. However, several SNP effects were significantly different from their counterparts in LMMs analyses. We suggest that fitting GLMMs with Wald's test on a pre-selected subset of SNPs obtained from logistic regression models can ensure the balance between the speed of analyses and the accuracy of parameters.

Abstract WP216: "BEAST" at the University of Virginia: Demographic and Phenotypic Data of Patients Contributing to a Biorepository to Establish the Etiology of Sinovenous Thrombosis

Introduction: Cerebral venous sinus thrombosis (CVST) occurs in 3-4 per 1 million individuals per year, accounting for approximately 1% of all strokes. Multiple etiologic risk factors for CVST have been identified, with known inherited thrombophilias accounting for 22% of cases. In 15% of cases, no known risk factor is identified. Studying the genetics of CVST holds the potential to identify at-risk groups, determine disease severity and prognosis, and consider novel therapies. BEAST is an international effort to identify genetic determinants of CVST, from which a recent discovery genome-wide association study (GWAS) identified 2 new associated loci. Methods: We are enrolling patients at least 18 years of age with a diagnosis of CVST who are willing to provide informed consent and a biospecimen to a central DNA repository. Patients are identified prospectively in clinical practice, and retrospectively using the Univ of Virginia clinical data repository. Results: Since 2012, twenty-eight patients have been enrolled. Demographic and phenotypic data are presented in the Table. Patients range in age from 19 to 65 years, with a mean of 40.5 (SD 14). Headache was the most common presenting symptom, occurring in 60%, followed by seizure (25%), mental status disturbance (21%), aphasia (11%) and mono- or hemiparesis (7%). Imaging revealed focal cerebral edema and/or venous infarction in 7 patients (25%) and hemorrhage in 5 patients (18%); no arteriovenous fistulae were identified. Acute treatments included intravenous or low molecular weight heparin (25/28, 89%) and anti-epileptic medications (7/28, 25%); three patients underwent local thrombolysis or endovascular intervention (11%). Conclusion: Understanding the association between phenotype and genetic determinants of CVST has the potential to advance the diagnosis and management of this challenging entity. Enrollment in BEAST continues and a replication cohort GWAS is anticipated in the near future.

Genome-wide association study in an admixed case series reveals IL12A as a new candidate in Behçet disease.

IntroductionThe etiology of Behçet’s disease (BD) is unknown, but widely considered an excessive T-cell mediated inflammatory response in a genetically susceptible host. Recent genome-wide association studies (GWAS) have shown limited number of novel loci-associations. The rarity and unequal distribution of the disease prevalence amongst different ethnic backgrounds have hampered the use of GWAS in cohorts of mixed ethnicity and sufficient sample size. However, novel statistical approaches have now enabled GWAS in admixed cohorts.MethodsWe ran a GWAS on 336 BD cases and 5,843 controls. The cases consisted of Western Europeans, Middle Eastern and Turkish individuals. Participants from the Generation R study, a multiethnic birth cohort in Rotterdam, The Netherlands were used as controls. All samples were genotyped and data was combined. Linear regression models were corrected for population stratification using Genomic Principal Components and Linear Mixed Modelling. Meta-analysis was performed on selected results previously published.ResultsWe identified SNPs associated at genome-wide significant level mapping to the 6p21.33 (HLA) region. In addition to this known signal two potential novel associations on chromosomes 6 and 18 were identified, yet with low minor allele frequencies. Extended meta-analysis reveal a GWS association with the IL12A variant rs17810546 on chromosome 3.DiscussionWe demonstrate that new statistical techniques enable GWAS analyses in a limited sized cohort of mixed ethnicity. After implementation, we confirmed the central role of the HLA region in the disease and identified new regions of interest. Moreover, we validated the association of a variant in the IL2A gene by meta-analysis with previous work. These findings enhance our knowledge of genetic associations and BD, and provide further justification for pursuing collective initiatives in genetic studies given the low prevalence of this and other rare diseases.

Extent of Height Variability Explained by Known Height-Associated Genetic Variants in an Isolated Population of the Adriatic Coast of Croatia

BackgroundHuman height is a classical example of a polygenic quantitative trait. Recent large-scale genome-wide association studies (GWAS) have identified more than 200 height-associated loci, though these variants explain only 2∼10% of overall variability of normal height. The objective of this study was to investigate the variance explained by these loci in a relatively isolated population of European descent with limited admixture and homogeneous genetic background from the Adriatic coast of Croatia.Methodology/Principal FindingsIn a sample of 1304 individuals from the island population of Hvar, Croatia, we performed genome-wide SNP typing and assessed the variance explained by genetic scores constructed from different panels of height-associated SNPs extracted from five published studies. The combined information of the 180 SNPs reported by Lango Allen el al. explained 7.94% of phenotypic variation in our sample. Genetic scores based on 20∼50 SNPs reported by the remaining individual GWA studies explained 3∼5% of height variance. These percentages of variance explained were within ranges comparable to the original studies and heterogeneity tests did not detect significant differences in effect size estimates between our study and the original reports, if the estimates were obtained from populations of European descent.Conclusions/SignificanceWe have evaluated the portability of height-associated loci and the overall fitting of estimated effect sizes reported in large cohorts to an isolated population. We found proportions of explained height variability were comparable to multiple reference GWAS in cohorts of European descent. These results indicate similar genetic architecture and comparable effect sizes of height loci among populations of European descent.

Fine-mapping in African Americans of 8 recently discovered genetic loci for plasma lipids: the Jackson Heart Study.

Genome-wide association studies in cohorts of European descent have identified novel genomic regions as associated with lipids, but their relevance in African Americans remains unclear. We genotyped 8 index single nucleotide polymorphisms (SNPs) and 488 tagging SNPs across 8 novel lipid loci in the Jackson Heart Study, a community-based cohort of 4605 African Americans. For each trait, we calculated residuals adjusted for age, sex, and global ancestry and performed multivariable linear regression to detect genotype-phenotype association with adjustment for local ancestry. To explore admixture effects, we conducted stratified analyses in individuals with a high probability of 2 African ancestral alleles or at least 1 European allele at each locus. We confirmed 2 index SNPs as associated with lipid traits in African Americans, with suggestive association for 3 more. However, the effect sizes for 4 of the 5 associated SNPs were larger in the European local ancestry subgroup compared with the African local ancestry subgroup, suggesting that the replication is driven by European ancestry segments. Through fine-mapping, we discovered 3 new SNPs with significant associations, 2 with consistent effect on triglyceride levels across ancestral groups: rs636523 near DOCK7/ANGPTL3 and rs780093 in GCKR. African linkage disequilibrium patterns did not assist in narrowing association signals. We confirm that 5 genetic regions associated with lipid traits in European-derived populations are relevant in African Americans. To further evaluate these loci, fine-mapping in larger African American cohorts and/or resequencing will be required.

Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium

Erythrocyte measures are heritable and have important health implications, yet their genetic determinants are largely unknown. We performed genome-wide association analyses in 24,167 European-ancestry individuals for six erythrocyte traits and identified associations at 23 loci (P values 5×10-8 to 1×10-57). Replication testing in an independent set of 9,456 European-ancestry individuals showed strong evidence of association in all 23 loci in meta-analysis of the discovery and replication cohorts. Our findings include previously identified loci (HBS1L/MYB, HFE, TMPRSS6, TFR2, SPTA1) and novel associations (EPO, TFRC, SH2B3, and 15 other loci). This study has identified novel determinants of erythrocyte traits, offering insight into common variants underlying variation in erythrocyte measures.