Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score--the CoLaus Study.

AIMS/HYPOTHESIS: Several susceptibility genes for type 2 diabetes have been discovered recently. Individually, these genes increase the disease risk only minimally. The goals of the present study were to determine, at the population level, the risk of diabetes in individuals who carry risk alleles within several susceptibility genes for the disease and the added value of this genetic information over the clinical predictors. METHODS: We constructed an additive genetic score using the most replicated single-nucleotide polymorphisms (SNPs) within 15 type 2 diabetes-susceptibility genes, weighting each SNP with its reported effect. We tested this score in the extensively phenotyped population-based cross-sectional CoLaus Study in Lausanne, Switzerland (n = 5,360), involving 356 diabetic individuals. RESULTS: The clinical predictors of prevalent diabetes were age, BMI, family history of diabetes, WHR, and triacylglycerol/HDL-cholesterol ratio. After adjustment for these variables, the risk of diabetes was 2.7 (95% CI 1.8-4.0, p = 0.000006) for individuals with a genetic score within the top quintile, compared with the bottom quintile. Adding the genetic score to the clinical covariates improved the area under the receiver operating characteristic curve slightly (from 0.86 to 0.87), yet significantly (p = 0.002). BMI was similar in these two extreme quintiles. CONCLUSIONS/INTERPRETATION: In this population, a simple weighted 15 SNP-based genetic score provides additional information over clinical predictors of prevalent diabetes. At this stage, however, the clinical benefit of this genetic information is limited.

Current genetic data do not improve the prediction of type 2 diabetes mellitus: the CoLaus study.

CONTEXT: Several genetic risk scores to identify asymptomatic subjects at high risk of developing type 2 diabetes mellitus (T2DM) have been proposed, but it is unclear whether they add extra information to risk scores based on clinical and biological data. OBJECTIVE: The objective of the study was to assess the extra clinical value of genetic risk scores in predicting the occurrence of T2DM. DESIGN: This was a prospective study, with a mean follow-up time of 5 yr. SETTING AND SUBJECTS: The study included 2824 nondiabetic participants (1548 women, 52 ± 10 yr). MAIN OUTCOME MEASURE: Six genetic risk scores for T2DM were tested. Four were derived from the literature and two were created combining all (n = 24) or shared (n = 9) single-nucleotide polymorphisms of the previous scores. A previously validated clinic + biological risk score for T2DM was used as reference. RESULTS: Two hundred seven participants (7.3%) developed T2DM during follow-up. On bivariate analysis, no differences were found for all but one genetic score between nondiabetic and diabetic participants. After adjusting for the validated clinic + biological risk score, none of the genetic scores improved discrimination, as assessed by changes in the area under the receiver-operating characteristic curve (range -0.4 to -0.1%), sensitivity (-2.9 to -1.0%), specificity (0.0-0.1%), and positive (-6.6 to +0.7%) and negative (-0.2 to 0.0%) predictive values. Similarly, no improvement in T2DM risk prediction was found: net reclassification index ranging from -5.3 to -1.6% and nonsignificant (P ≥ 0.49) integrated discrimination improvement. CONCLUSIONS: In this study, adding genetic information to a previously validated clinic + biological score does not seem to improve the prediction of T2DM.

Prédire la survenue d'un diabète: la place de scores cliniques et/ou génétiques [Genetic and/or clinical scores to anticipate the onset of diabetes]

Diabetes represents an important health burden on our society: for example in Lausanne (Switzerland) 16% of the adult population have abnormal glucose homeostasis and 6% have diabetes, of which about a third is not aware. Some guidelines identify the "at risk" population for which screening seems indicated. Simple clinical scores have been developed at allow to better estimate the risk of diabetes and hence to potentially better target screening of the disease. The recent discovery of more that 18 genetic variants associated with an increased risk to develop the diseased has allowed to include individual genotype into genetic risk scores. We will discuss in this article the usefulness of these genetic score, how they compare to clinical score, their implication for clinical practice as well as their potential ethical or economical consequences.

Contribution of genetic background, traditional risk factors, and HIV-related factors to coronary artery disease events in HIV-positive persons.

BACKGROUND: Persons infected with human immunodeficiency virus (HIV) have increased rates of coronary artery disease (CAD). The relative contribution of genetic background, HIV-related factors, antiretroviral medications, and traditional risk factors to CAD has not been fully evaluated in the setting of HIV infection. METHODS: In the general population, 23 common single-nucleotide polymorphisms (SNPs) were shown to be associated with CAD through genome-wide association analysis. Using the Metabochip, we genotyped 1875 HIV-positive, white individuals enrolled in 24 HIV observational studies, including 571 participants with a first CAD event during the 9-year study period and 1304 controls matched on sex and cohort. RESULTS: A genetic risk score built from 23 CAD-associated SNPs contributed significantly to CAD (P = 2.9 × 10(-4)). In the final multivariable model, participants with an unfavorable genetic background (top genetic score quartile) had a CAD odds ratio (OR) of 1.47 (95% confidence interval [CI], 1.05-2.04). This effect was similar to hypertension (OR = 1.36; 95% CI, 1.06-1.73), hypercholesterolemia (OR = 1.51; 95% CI, 1.16-1.96), diabetes (OR = 1.66; 95% CI, 1.10-2.49), ≥ 1 year lopinavir exposure (OR = 1.36; 95% CI, 1.06-1.73), and current abacavir treatment (OR = 1.56; 95% CI, 1.17-2.07). The effect of the genetic risk score was additive to the effect of nongenetic CAD risk factors, and did not change after adjustment for family history of CAD. CONCLUSIONS: In the setting of HIV infection, the effect of an unfavorable genetic background was similar to traditional CAD risk factors and certain adverse antiretroviral exposures. Genetic testing may provide prognostic information complementary to family history of CAD.

Contribution de l'étude CoLaus à l'élucidation des déterminants de l'acide urique sérique [Contribution of the CoLaus study to decipher the determinants of serum uric acid].

Asymptomatic hyperuricemia affects one in five adults in the general population and is associated with elevated cardiovascular risk. It is however not clear whether asymptomatic hyperuricemia is a cause or simply a marker of conditions associated with high cardiovascular risk. Sex, age, obesity, renal function and selected drugs are major determinants of serum uric acid. Moreover, recent genome-wide association studies have identified new genes involved in the control of serum uric acid levels, in particular SLC2A9, which encodes a urate transporter located in the kidney. A genetic score based on several genetic variants associated with serum uric acid is strongly associated with the risk of gout, but not with cardiovascular events so far.

Impact of single nucleotide polymorphisms and of clinical risk factors on new‐onset diabetes mellitus in HIV‐infected individuals.

BACKGROUND: Metabolic complications, including cardiovascular events and diabetes mellitus (DM), are a major long-term concern in human immunodeficiency virus (HIV)-infected individuals. Recent genome-wide association studies have reliably associated multiple single nucleotide polymorphisms (SNPs) to DM in the general population. METHODS: We evaluated the contribution of 22 SNPs identified in genome-wide association studies and of longitudinally measured clinical factors to DM. We genotyped all 94 white participants in the Swiss HIV Cohort Study who developed DM from 1 January 1999 through 31 August 2009 and 550 participants without DM. Analyses were based on 6054 person-years of follow-up and 13,922 measurements of plasma glucose. RESULTS: The contribution to DM risk explained by SNPs (14% of DM variability) was larger than the contribution to DM risk explained by current or cumulative exposure to different antiretroviral therapy combinations (3% of DM variability). Participants with the most unfavorable genetic score (representing 12% and 19% of the study population, respectively, when applying 2 different genetic scores) had incidence rate ratios for DM of 3.80 (95% confidence interval [CI], 2.05-7.06) and 2.74 (95% CI, 1.53-4.88), respectively, compared with participants with a favorable genetic score. However, addition of genetic data to clinical risk factors that included body mass index only slightly improved DM prediction. CONCLUSIONS: In white HIV-infected persons treated with antiretroviral therapy, the DM effect of genetic variants was larger than the potential toxic effects of antiretroviral therapy. SNPs contributed significantly to DM risk, but their addition to a clinical model improved DM prediction only slightly, similar to studies in the general population.

Contribution de l'étude CoLaus à l'élucidation des déterminants de l'acide urique sérique. [Contribution of the CoLaus study to decipher the determinants of serum uric acid].

Asymptomatic hyperuricemia affects one in five adults in the general population and is associated with elevated cardiovascular risk. It is however not clear whether asymptomatic hyperuricemia is a cause or simply a marker of conditions associated with high cardiovascular risk. Sex, age, obesity, renal function and selected drugs are major determinants of serum uric acid. Moreover, recent genome-wide association studies have identified new genes involved in the control of serum uric acid levels, in particular SLC2A9, which encodes a urate transporter located in the kidney. A genetic score based on several genetic variants associated with serum uric acid is strongly associated with the risk of gout, but not with cardiovascular events so far.

No evidence for a causal link between uric acid and type 2 diabetes: a Mendelian randomisation approach.

AIMS/HYPOTHESIS: Epidemiological and experimental evidence suggests that uric acid has a role in the aetiology of type 2 diabetes. Using a Mendelian randomisation approach, we investigated whether there is evidence for a causal role of serum uric acid for development of type 2 diabetes. METHODS: We examined the associations of serum-uric-acid-raising alleles of eight common variants recently identified in genome-wide association studies and summarised this in a genetic score with type 2 diabetes in case-control studies including 7,504 diabetes patients and 8,560 non-diabetic controls. We compared the observed effect size to that expected based on: (1) the association between the genetic score and uric acid levels in non-diabetic controls; and (2) the meta-analysed uric acid level to diabetes association. RESULTS: The genetic score showed a linear association with uric acid levels, with a difference of 12.2 μmol/l (95% CI 9.3, 15.1) by score tertile. No significant associations were observed between the genetic score and potential confounders. No association was observed between the genetic score and type 2 diabetes with an OR of 0.99 (95% CI 0.94, 1.04) per score tertile, significantly different (p = 0.046) from that expected (1.04 [95% CI 1.03, 1.05]) based on the observed uric acid difference by score tertile and the uric acid to diabetes association of 1.21 (95% CI 1.14, 1.29) per 60 μmol/l. CONCLUSIONS/INTERPRETATION: Our results do not support a causal role of serum uric acid for the development of type 2 diabetes and limit the expectation that uric-acid-lowering drugs will be effective in the prevention of type 2 diabetes.

Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.

BACKGROUND AND PURPOSE: Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors. METHODS: The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke. RESULTS: In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P<10(-4)). CONCLUSIONS: The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Genetic linkage of Bietti crystallin corneoretinal dystrophy to chromosome 4q35.

Bietti crystalline corneoretinal dystrophy (BCD) is an autosomal recessive retinal degeneration characterized by multiple glistening intraretinal dots scattered over the fundus, degeneration of the retina, and sclerosis of the choroidal vessels, ultimately resulting in progressive night blindness and constriction of the visual field. Although BCD has been associated with abnormalities in fatty-acid metabolism and absence of fatty-acid binding by two cytosolic proteins, the genetic basis of BCD is unknown. We report linkage of the BCD locus to D4S426 (maximum LOD score [Z(max)] 4.81; recombination fraction [straight theta] 0), D4S2688 (Zmax=3.97; straight theta=0), and D4S2299 (Zmax=5.31; straight theta=0), on chromosome 4q35-4qtel. Multipoint analysis confirmed linkage to the region telomeric of D4S1652 with a Z(max) of 5.3 located 4 cM telomeric of marker D4S2930.

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.

Blood pressure is a heritable trait influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (≥140 mm Hg systolic blood pressure or  ≥90 mm Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention.

Genetic relationships between suicide attempts, suicidal ideation and major psychiatric disorders: A genome-wide association and polygenic scoring study.

Epidemiological studies have recognized a genetic diathesis for suicidal behavior, which is independent of other psychiatric disorders. Genome-wide association studies (GWAS) on suicide attempt (SA) and ideation have failed to identify specific genetic variants. Here, we conduct further GWAS and for the first time, use polygenic score analysis in cohorts of patients with mood disorders, to test for common genetic variants for mood disorders and suicide phenotypes. Genome-wide studies for SA were conducted in the RADIANT and GSK-Munich recurrent depression samples and London Bipolar Affective Disorder Case-Control Study (BACCs) then meta-analysis was performed. A GWAS on suicidal ideation during antidepressant treatment had previously been conducted in the Genome Based Therapeutic Drugs for Depression (GENDEP) study. We derived polygenic scores from each sample and tested their ability to predict SA in the mood disorder cohorts or ideation status in the GENDEP study. Polygenic scores for major depressive disorder, bipolar disorder and schizophrenia from the Psychiatric Genomics Consortium were used to investigate pleiotropy between psychiatric disorders and suicide phenotypes. No significant evidence for association was detected at any SNP in GWAS or meta-analysis. Polygenic scores for major depressive disorder significantly predicted suicidal ideation in the GENDEP pharmacogenetics study and also predicted SA in a combined validation dataset. Polygenic scores for SA showed no predictive ability for suicidal ideation. Polygenic score analysis suggests pleiotropy between psychiatric disorders and suicidal ideation whereas the tendency to act on such thoughts may have a partially independent genetic diathesis. © 2014 Wiley Periodicals, Inc.

Genetic Loci Associated with C-reactive Protein Levels and Risk of Coronary Heart Disease.

CONTEXT: Plasma levels of C-reactive protein (CRP) are independently associated with risk of coronary heart disease, but whether CRP is causally associated with coronary heart disease or merely a marker of underlying atherosclerosis is uncertain. OBJECTIVE: To investigate association of genetic loci with CRP levels and risk of coronary heart disease. DESIGN, SETTING, AND PARTICIPANTS: We first carried out a genome-wide association (n = 17,967) and replication study (n = 13,615) to identify genetic loci associated with plasma CRP concentrations. Data collection took place between 1989 and 2008 and genotyping between 2003 and 2008. We carried out a mendelian randomization study of the most closely associated single-nucleotide polymorphism (SNP) in the CRP locus and published data on other CRP variants involving a total of 28,112 cases and 100,823 controls, to investigate the association of CRP variants with coronary heart disease. We compared our finding with that predicted from meta-analysis of observational studies of CRP levels and risk of coronary heart disease. For the other loci associated with CRP levels, we selected the most closely associated SNP for testing against coronary heart disease among 14,365 cases and 32,069 controls. MAIN OUTCOME MEASURE: Risk of coronary heart disease. RESULTS: Polymorphisms in 5 genetic loci were strongly associated with CRP levels (% difference per minor allele): SNP rs6700896 in LEPR (-14.8%; 95% confidence interval [CI], -17.6% to -12.0%; P = 6.2 x 10(-22)), rs4537545 in IL6R (-11.5%; 95% CI, -14.4% to -8.5%; P = 1.3 x 10(-12)), rs7553007 in the CRP locus (-20.7%; 95% CI, -23.4% to -17.9%; P = 1.3 x 10(-38)), rs1183910 in HNF1A (-13.8%; 95% CI, -16.6% to -10.9%; P = 1.9 x 10(-18)), and rs4420638 in APOE-CI-CII (-21.8%; 95% CI, -25.3% to -18.1%; P = 8.1 x 10(-26)). Association of SNP rs7553007 in the CRP locus with coronary heart disease gave an odds ratio (OR) of 0.98 (95% CI, 0.94 to 1.01) per 20% lower CRP level. Our mendelian randomization study of variants in the CRP locus showed no association with coronary heart disease: OR, 1.00; 95% CI, 0.97 to 1.02; per 20% lower CRP level, compared with OR, 0.94; 95% CI, 0.94 to 0.95; predicted from meta-analysis of the observational studies of CRP levels and coronary heart disease (z score, -3.45; P < .001). SNPs rs6700896 in LEPR (OR, 1.06; 95% CI, 1.02 to 1.09; per minor allele), rs4537545 in IL6R (OR, 0.94; 95% CI, 0.91 to 0.97), and rs4420638 in the APOE-CI-CII cluster (OR, 1.16; 95% CI, 1.12 to 1.21) were all associated with risk of coronary heart disease. CONCLUSION: The lack of concordance between the effect on coronary heart disease risk of CRP genotypes and CRP levels argues against a causal association of CRP with coronary heart disease.

Genetic heterogeneity of the Coppock-like cataract: a mutation in CRYBB2 on chromosome 22q11.2.

PURPOSE: To identify the genetic defect for the Coppock-like cataract (CCL) affecting a Swiss family, which defect was unlinked to the chromosome 2q33-35 CCL locus. METHODS: A large family was characterized for linkage analysis by slit lamp examination or by the review of drawings made before cataract extraction. The affection status was attributed before genotyping, and the genotyping was masked to the affection status. Two-point and multipoint linkage analyses were performed using the MLINK and the LINKMAP components of the LINKAGE program package (ver. 5.1), respectively. Mutational analysis of candidate genes was performed by a combination of direct cycle sequencing and an amplification refractory mutation system assay. RESULTS: Ten individuals were affected with the CCL phenotype. The disease was autosomal dominant and appeared to be fully penetrant. A new CCL locus was identified on chromosome 22q11.2 within a 11.67-cM interval (maximum lod score [Zmax] = 4.14; theta = 0). Mutational analysis of the CRYBB2 candidate gene identified a disease-causing mutation in exon 6. This sequence change was identical with that previously described to be associated with the cerulean cataract, a clinically distinct entity. CONCLUSIONS: The CCL phenotype is genetically heterogeneous with a second gene on chromosome 22q11.2, CRYBB2. The CCL and the cerulean cataract are two distinct clinical entities associated with the same genetic defect. This work provides evidence for a modifier factor that influences cataract formation and that remains to be identified.