Assessment of pharmacogenetic tests: presenting measures of clinical validity and potential population impact in association studies.

The progressing discovery of genetic variants associated with drug-related adverse events has raised expectations for pharmacogenetic tests to improve drug efficacy and safety. To further the use of pharmacogenetics in health care, tests with sufficient potential to improve efficacy and safety, as reflected by good clinical validity and population impact, need to be identified. The potential benefit of pharmacogenetic tests is often concluded from the strength of the association between the variant and the adverse event; measures of clinical validity are generally not reported. This paper describes measures of clinical validity and potential population health impact that can be calculated from association studies. We explain how these measures are influenced by the strength of the association and by the frequencies of the variant and the adverse event. The measures are illustrated using examples of testing for HLA-B*5701 associated with abacavir-induced hypersensitivity and SLCO1B1 c.521T>C (*5) associated with simvastatin-induced adverse events.

Value of EUS in Determining Curative Resectability in Reference to CT and FDG-PET: The Optimal Sequence in Preoperative Staging of Esophageal Cancer?

BACKGROUND: The separate value of endoscopic ultrasonography (EUS), multidetector computed tomography (CT), and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) in the optimal sequence in staging esophageal cancer has not been investigated adequately. METHODS: The staging records of 216 consecutive operable patients with esophageal cancer were reviewed blindly. Different staging strategies were analyzed, and the likelihood ratio (LR) of each module was calculated conditionally on individual patient characteristics. A logistic regression approach was used to determine the most favorable staging strategy. RESULTS: Initial EUS results were not significantly related to the LRs of initial CT and FDG-PET results. The positive LR (LR+) of EUS-fine-needle aspiration (FNA) was 4, irrespective of CT and FDG-PET outcomes. The LR+ of FDG-PET varied from 13 (negative CT) to 6 (positive CT). The LR+ of CT ranged from 3-4 (negative FDG-PET) to 2-3 (positive FDG-PET). Age, histology, and tumor length had no significant impact on the LRs of the three diagnostic tests. CONCLUSIONS: This study argues in favor of PET/CT rather than EUS as a predictor of curative resectability in esophageal cancer. EUS does not correspond with either CT or FDG-PET. LRs of FDG-PET were substantially different between subgroups of negative and positive CT results and vice versa.

[Biobanks and the return of results to donors]. / Biobanken en de terugkoppeling van onderzoeksbevindingen aan donoren.

Biobanks should return clinically significant and actionable research findings to donors who have given physical material to the biobank. Because the clinical significance of a research finding is hard to determine for the individual donor, a procedure to decide on clinical significance should be incorporated into a structure for the actual feedback of research results. Most published studies show that donors expect return of individual research results, but there is almost no experience with it. Explorative questionnaire-based research among Dutch biobanks from the BioBanking Medical Research Infrastructure (BBMRI.NL) shows that a substantial group of biobanks can return individual research findings from data analysis. On the basis of these experiences a return of results policy may be drafted that answers to the interests of donors and the possibilities of biobanks.

Prediction model for knee osteoarthritis incidence, including clinical, genetic and biochemical risk factors.

OBJECTIVE: To develop and validate a prognostic model for incident knee osteoarthritis (KOA) in a general population and determine the value of different risk factor groups to prediction. METHODS: The prognostic model was developed in 2628 individuals from the Rotterdam Study-I (RS-I). Univariate and multivariate analyses were performed for questionnaire/easily obtainable variables, imaging variables, genetic and biochemical markers. The extended multivariate model was tested on discrimination (receiver operating characteristic curve and area under the curve (AUC)) in two other population-based cohorts: Rotterdam Study-II and Chingford Study. RESULTS: In RS-I, there was moderate predictive value for incident KOA based on the genetic score alone in subjects aged <65 years (AUC 0.65), while it was only 0.55 for subjects aged ≥65 years. The AUC for gender, age and body mass index (BMI) in prediction for KOA was 0.66. Addition of the questionnaire variables, genetic score or biochemical marker urinary C-terminal cross-linked telopeptide of type II collagen to the model did not change the AUC. However, when adding the knee baseline KL score to the model the AUC increased to 0.79. Applying external validation, similar results were observed in the Rotterdam Study-II and the Chingford Study. CONCLUSIONS: Easy obtainable 'Questionnaire' variables, genetic markers, OA at other joint sites and biochemical markers add only modestly to the prediction of KOA incidence using age, gender and BMI in an elderly population. Doubtful minor radiographic degenerative features in the knee, however, are a very strong predictor of future KOA. This is an important finding, as many radiologists do not report minor degenerative changes in the knee.

A K(ATP) channel gene effect on sleep duration: from genome-wide association studies to function in Drosophila.

Humans sleep approximately a third of their lifetime. The observation that individuals with either long or short sleep duration show associations with metabolic syndrome and psychiatric disorders suggests that the length of sleep is adaptive. Although sleep duration can be influenced by photoperiod (season) and phase of entrainment (chronotype), human familial sleep disorders indicate that there is a strong genetic modulation of sleep. Therefore, we conducted high-density genome-wide association studies for sleep duration in seven European populations (N=4251). We identified an intronic variant (rs11046205; P=3.99 × 10(-8)) in the ABCC9 gene that explains ≈5% of the variation in sleep duration. An influence of season and chronotype on sleep duration was solely observed in the replication sample (N=5949). Meta-analysis of the associations found in a subgroup of the replication sample, chosen for season of entry and chronotype, together with the discovery results showed genome-wide significance. RNA interference knockdown experiments of the conserved ABCC9 homologue in Drosophila neurons renders flies sleepless during the first 3 h of the night. ABCC9 encodes an ATP-sensitive potassium channel subunit (SUR2), serving as a sensor of intracellular energy metabolism.

Meta-analysis of genome-wide association studies for personality.

Personality can be thought of as a set of characteristics that influence people's thoughts, feelings and behavior across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in 10 discovery samples (17,375 adults) and five in silico replication samples (3294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data of ≈ 2.4M single-nucleotide polymorphisms (SNPs; directly typed and imputed using HapMap data) were available. In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P=2.8 × 10(-8) and 3.1 × 10(-8)) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P=4.9 × 10(-8)). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.

Pregnancy in multiple sclerosis: clinical and self-report scales.

Relapse rate is decreased during pregnancy in multiple sclerosis (MS). Risk for postpartum relapse is increased in the first 3 months after delivery. We aimed to study clinical course of MS around pregnancy, using clinical as well as self-report scales, including data on quality of life (QoL), and to identify clinical factors predisposing for postpartum relapse. We performed a prospective, longitudinal study among 35 MS patients and 20 controls. In patients we assessed expanded disability status scale (EDSS), the Guy's neurological disability scale (GNDS) and the multiple sclerosis impact scale 29 (MSIS-29). In patients and controls we assessed the MOS 36 item short form health survey questionnaire (SF36), consisting of eight domains. The previously described surge in relapses after delivery was also obvious in this study (p = 0.005). At group level EDSS and MSIS-29 did not show overt fluctuations over time. The GNDS, however, improved during the third trimester, compared to the first trimester (p = 0.003). A concomitant improvement in the SF36 domains vitality (p < 0.001) and general health (p = 0.001) was found in patients. At the final visit, at least 9 months after delivery, no worsening of EDSS, GNDS, MSIS-29 or SF36 was observed compared with the (for MS, beneficial) third trimester. Duration of disease, relapses in the year preceding pregnancy or relapses during pregnancy were not associated with postpartum relapse. QoL is improved during pregnancy. Although relapse rate was increased directly after delivery, in the mid long term after delivery no adverse effects of pregnancy on MS were found.

A genome-wide linkage study of individuals with high scores on NEO personality traits.

The NEO-Five-Factor Inventory divides human personality traits into five dimensions: neuroticism, extraversion, openness, conscientiousness and agreeableness. In this study, we sought to identify regions harboring genes with large effects on the five NEO personality traits by performing genome-wide linkage analysis of individuals scoring in the extremes of these traits (>90th percentile). Affected-only linkage analysis was performed using an Illumina 6K linkage array in a family-based study, the Erasmus Rucphen Family study. We subsequently determined whether distinct, segregating haplotypes found with linkage analysis were associated with the trait of interest in the population. Finally, a dense single-nucleotide polymorphism genotyping array (Illumina 318K) was used to search for copy number variations (CNVs) in the associated regions. In the families with extreme phenotype scores, we found significant evidence of linkage for conscientiousness to 20p13 (rs1434789, log of odds (LOD)=5.86) and suggestive evidence of linkage (LOD >2.8) for neuroticism to 19q, 21q and 22q, extraversion to 1p, 1q, 9p and12q, openness to 12q and 19q, and agreeableness to 2p, 6q, 17q and 21q. Further analysis determined haplotypes in 21q22 for neuroticism (P-values = 0.009, 0.007), in 17q24 for agreeableness (marginal P-value = 0.018) and in 20p13 for conscientiousness (marginal P-values = 0.058, 0.038) segregating in families with large contributions to the LOD scores. No evidence for CNVs in any of the associated regions was found. Our findings imply that there may be genes with relatively large effects involved in personality traits, which may be identified with next-generation sequencing techniques.

Genome-wide association analysis of coffee drinking suggests association with CYP1A1/CYP1A2 and NRCAM.

Coffee consumption is a model for addictive behavior. We performed a meta-analysis of genome-wide association studies (GWASs) on coffee intake from 8 Caucasian cohorts (N=18 176) and sought replication of our top findings in a further 7929 individuals. We also performed a gene expression analysis treating different cell lines with caffeine. Genome-wide significant association was observed for two single-nucleotide polymorphisms (SNPs) in the 15q24 region. The two SNPs rs2470893 and rs2472297 (P-values=1.6 × 10(-11) and 2.7 × 10(-11)), which were also in strong linkage disequilibrium (r(2)=0.7) with each other, lie in the 23-kb long commonly shared 5' flanking region between CYP1A1 and CYP1A2 genes. CYP1A1 was found to be downregulated in lymphoblastoid cell lines treated with caffeine. CYP1A1 is known to metabolize polycyclic aromatic hydrocarbons, which are important constituents of coffee, whereas CYP1A2 is involved in the primary metabolism of caffeine. Significant evidence of association was also detected at rs382140 (P-value=3.9 × 10(-09)) near NRCAM-a gene implicated in vulnerability to addiction, and at another independent hit rs6495122 (P-value=7.1 × 10(-09))-an SNP associated with blood pressure-in the 15q24 region near the gene ULK3, in the meta-analysis of discovery and replication cohorts. Our results from GWASs and expression analysis also strongly implicate CAB39L in coffee drinking. Pathway analysis of differentially expressed genes revealed significantly enriched ubiquitin proteasome (P-value=2.2 × 10(-05)) and Parkinson's disease pathways (P-value=3.6 × 10(-05)).

Risk prediction models: a framework for assessment.

BACKGROUND: Medical risk prediction models estimate the likelihood of future health-related events. Many make use of information derived from analysis of the genome. Models predict health outcomes such as cardiovascular disease, stroke and cancer, and for some conditions several models exist. Although risk models can help decision-making in clinical medicine and public health, they can also be harmful, for example, by misdirecting clinical effort away from those who are most likely to benefit towards people with less need, thus exacerbating health inequalities. DISCUSSION: Risk prediction models need careful assessment before implementation, but the current approach to their development, evaluation and implementation is inappropriate. As a result, some models are pressed into use before it is clear whether they are suitable, while in other cases there is confusion about which model to use. This paper proposes an approach to the appraisal of risk-scoring models, based on a conference of UK experts. SUMMARY: By specifying what needs to be known before a model can be judged suitable for translation from research into practice, we can ensure that useful models are taken up promptly, that less well-proven ones undergo further evaluation and that resources are not wasted on ineffective ones.

The sense and nonsense of direct-to-consumer genetic testing for cardiovascular disease.

Expectations are high that increasing knowledge of the genetic basis of cardiovascular disease will eventually lead to personalised medicine-to preventive and therapeutic interventions that are targeted to at-risk individuals on the basis of their genetic profiles. Most cardiovascular diseases are caused by a complex interplay of many genetic variants interacting with many non-genetic risk factors such as diet, exercise, smoking and alcohol consumption. Since several years, genetic susceptibility testing for cardiovascular diseases is being offered via the internet directly to consumers. We discuss five reasons why these tests are not useful, namely: (1) the predictive ability is still limited; (2) the risk models used by the companies are based on assumptions that have not been verified; (3) the predicted risks keep changing when new variants are discovered and added to the test; (4) the tests do not consider non-genetic factors in the prediction of cardiovascular disease risk; and (5) the test results will not change recommendations of preventive interventions. Predictive genetic testing for multifactorial forms of cardiovascular disease clearly lacks benefits for the public. Prevention of disease should therefore remain focused on family history and on non-genetic risk factors as diet and physical activity that can have the strongest impact on disease risk, regardless of genetic susceptibility.

Genetic risk profiles for depression and anxiety in adult and elderly cohorts.

The first generation of genome-wide association studies (GWA studies) for psychiatric disorders has led to new insights regarding the genetic architecture of these disorders. We now start to realize that a larger number of genes, each with a small contribution, are likely to explain the heritability of psychiatric diseases. The contribution of a large number of genes to complex traits can be analyzed with genome-wide profiling. In a discovery sample, a genetic risk profile for depression was defined based on a GWA study of 1738 adult cases and 1802 controls. The genetic risk scores were tested in two population-based samples of elderly participants. The genetic risk profiles were evaluated for depression and anxiety in the Rotterdam Study cohort and the Erasmus Rucphen Family (ERF) study. The genetic risk scores were significantly associated with different measures of depression and explained up to ∼0.7% of the variance in depression in Rotterdam Study and up to ∼1% in ERF study. The genetic score for depression was also significantly associated with anxiety explaining up to 2.1% in Rotterdam study. These findings suggest the presence of many genetic loci of small effect that influence both depression and anxiety. Remarkably, the predictive value of these profiles was as large in the sample of elderly participants as in the middle-aged samples.

The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data.

The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, ∼0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.

Insulin-resistance and metabolic syndrome are related to executive function in women in a large family-based study.

While type 2 diabetes is well-known to be associated with poorer cognitive performance, few studies have reported on the association of metabolic syndrome (MetS) and contributing factors, such as insulin-resistance (HOMA-IR), low adiponectin-, and high C-reactive protein (CRP)-levels. We studied whether these factors are related to cognitive function and which of the MetS components are independently associated. The study was embedded in an ongoing family-based cohort study in a Dutch population. All participants underwent physical examinations, biomedical measurements, and neuropsychological testing. Linear regression models were used to determine the association between MetS, HOMA-IR, adiponectin levels, CRP, and cognitive test scores. Cross-sectional analyses were performed in 1,898 subjects (mean age 48 years, 43% men). People with MetS had significantly higher HOMA-IR scores, lower adiponectin levels, and higher CRP levels. MetS and high HOMA-IR were associated with poorer executive function in women (P = 0.03 and P = 0.009). MetS and HOMA-IR are associated with poorer executive function in women.

Shared genetic factors in migraine and depression: evidence from a genetic isolate.

OBJECTIVE: To investigate the co-occurrence of migraine and depression and assess whether shared genetic factors may underlie both diseases. METHODS: Subjects were 2,652 participants of the Erasmus Rucphen Family genetic isolate study. Migraine was diagnosed using a validated 3-stage screening method that included a telephone interview. Symptoms of depression were assessed using the Center for Epidemiologic Studies Depression scale and the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). The contribution of shared genetic factors in migraine and depression was investigated by comparing heritability estimates for migraine with and without adjustment for symptoms of depression, and by comparing the heritability scores of depression between migraineurs and controls. RESULTS: We identified 360 migraine cases: 209 had migraine without aura (MO) and 151 had migraine with aura (MA). Odds ratios for depression in patients with migraine were 1.29 (95% confidence interval [CI] 0.98-1.70) for MO and 1.70 (95% CI 1.28-2.24) for MA. Heritability estimates were significant for all migraine (0.56), MO (0.77), and MA (0.96), and decreased after adjustment for symptoms of depression or use of antidepressant medication, in particular for MA. Comparison of the heritability scores for depression between patients with migraine and controls showed a genetic correlation between HADS-D score and MA. CONCLUSIONS: There is a bidirectional association between depression and migraine, in particular migraine with aura, which can be explained, at least partly, by shared genetic factors.

Genome-wide association scan for five major dimensions of personality.

Personality traits are summarized by five broad dimensions with pervasive influences on major life outcomes, strong links to psychiatric disorders and clear heritable components. To identify genetic variants associated with each of the five dimensions of personality we performed a genome-wide association (GWA) scan of 3972 individuals from a genetically isolated population within Sardinia, Italy. On the basis of the analyses of 362 129 single-nucleotide polymorphisms we found several strong signals within or near genes previously implicated in psychiatric disorders. They include the association of neuroticism with SNAP25 (rs362584, P=5 x 10(-5)), extraversion with BDNF and two cadherin genes (CDH13 and CDH23; Ps<5 x 10(-5)), openness with CNTNAP2 (rs10251794, P=3 x 10(-5)), agreeableness with CLOCK (rs6832769, P=9 x 10(-6)) and conscientiousness with DYRK1A (rs2835731, P=3 x 10(-5)). Effect sizes were small (less than 1% of variance), and most failed to replicate in the follow-up independent samples (N up to 3903), though the association between agreeableness and CLOCK was supported in two of three replication samples (overall P=2 x 10(-5)). We infer that a large number of loci may influence personality traits and disorders, requiring larger sample sizes for the GWA approach to confidently identify associated genetic variants.

Menopause impacts the relation of plasma adiponectin levels with the metabolic syndrome.

OBJECTIVE: Plasma adiponectin is negatively correlated with metabolic syndrome (MetS) components obesity and insulin sensitivity. Here, we set out to evaluate the effect of menopause on the association of plasma adiponectin with MetS. DESIGN: Data on plasma adiponectin and MetS were available from 2256 individuals participating in the Erasmus Rucphen Family study. Odds ratios for MetS were calculated by logistic regression analysis using plasma adiponectin quartiles. The discriminative accuracy of plasma adiponectin for MetS was determined by calculating the area under the curve (AUC) of receiver operator. Analyses were performed in women and men, pre- and postmenopausal women and younger and older men. RESULTS: Virtually all determinants of MetS differed significantly between groups. Low plasma adiponectin showed the highest risk for MetS in postmenopausal women (odds ratio = 18.6, 95% CI = 7.9-44.0). We observed a high discriminative accuracy of age and plasma adiponectin for MetS not only in postmenopausal women (AUC = 0.76) but also in other subgroups (AUC from 0.67 to 0.87). However, in all groups, the discriminative accuracy of age and body mass index (BMI) for MetS was similar to the discriminative accuracy of age and plasma adiponectin. CONCLUSIONS: Low plasma levels of adiponectin are associated with increased prevalence of MetS, especially in postmenopausal women. Age and BMI have similar discriminatory accuracies for presence of MetS when compared with age and plasma adiponectin. Thus, we conclude that the association of plasma adiponectin with MetS is significantly affected by menopause but challenge the additional value of adiponectin for the discriminatory accuracy for presence of MetS.

Callosal lesion predicts future attacks after clinically isolated syndrome.

BACKGROUND: Current MRI criteria can help predict a second attack after a clinically isolated syndrome (CIS). Given the known association between corpus callosum lesions (CC) and multiple sclerosis (MS), such lesions on MRI could provide additional predictive information. This study assessed whether the presence of CC lesion on MRI could, next to the modified Barkhof criteria, further enhance prediction of conversion from CIS to MS. METHODS: Follow-up study of 158 patients with CIS who underwent MRI after CIS was performed. MRI were scored for the Barkhof criteria and CC lesion. Patients were classified as having MS according to Poser criteria. Cox regression models were used for the time to conversion from CIS to MS. RESULTS: The Barkhof criteria and CC lesion were strongly associated with conversion to MS with hazard ratios (HR), respectively, of 2.6 (95% confidence interval [CI] 1.5-4.3) and 2.7 (95% CI 1.6-4.5). The HRs of CC lesion adjusted for the Barkhof criteria and the Barkhof criteria adjusted for CC lesion were similar (HRs 1.8, not significant). The combined prediction of the Barkhof criteria and CC lesion was 3.3 (95% CI 1.9-5.7). Patients not fulfilling the Barkhof criteria had a fourfold increased risk of MS (HR 3.8, 95% CI 1.5-9.3) when they had a lesion in the CC. CONCLUSIONS: Corpus callosum (CC) lesion and the Barkhof criteria both predicted conversion to multiple sclerosis (MS). When both variables were combined, the association was stronger. The assessment of CC lesion may be a useful additional tool for predicting conversion to MS in patients with clinically isolated syndrome.