Rare susceptibility variants for bipolar disorder suggest a role for G protein-coupled receptors

Bipolar disorder (BD) is a prevalent mood disorder that tends to cluster in families. Despite high heritability estimates, few genetic susceptibility factors have been identified over decades of genetic research. One possible interpretation for the shortcomings of previous studies to detect causative genes is that BD is caused by highly penetrant rare variants in many genes. We explored this hypothesis by sequencing the exomes of affected individuals from 40 well-characterized multiplex families. We identified rare variants segregating with affected status in many interesting genes, and found an enrichment of deleterious variants in G protein-coupled receptor (GPCR) family genes, which are important drug targets. Furthermore, we showed targeted downstream GPCR dysregulation for some of the variants that may contribute to disease pathology. Particularly interesting was the finding of a rare and functionally relevant nonsense mutation in the corticotropin-releasing hormone receptor 2 (CRHR2) gene that tracked with affected status in one family. By focusing on rare variants in informative families, we identified key biochemical pathways likely implicated in this complex disorder.

Pedigree selection and tests of linkage in a Hutterite asthma pedigree

We explored methods for kinship and linkage analysis in a Hutterite pedigree comprising 1,544 individuals, 72 of whom were diagnosed with asthma. Subpedigrees were selected by (a) identifying nuclear families containing asthmatics, (b) identifying couples with many asthmatic descendants in an ad hoc manner, and (c) finding the most recent common ancestors of all asthmatics. Markov chain Monte Carlo (MCMC) methods were used to estimate allele sharing in the larger subpedigrees and transmission/disequilibrium tests were performed on nuclear families. On chromosome 5q near the cytokine cluster, modest evidence for linkage to asthma was obtained. Using MCMC, we were able to evaluate the evidence for linkage in complex subpedigrees of several hundred individuals, and hence, incorporate some of the co-ancestry of this founder population.

Imprinting and deviation from Mendelian transmission ratios

Deviations from a Mendelian 1:1 transmission ratio have been observed in human and mouse chromosomes. With few exceptions, the underlying mechanism of the transmission-ratio distortion remains obscure. We tested a hypothesis that grandparental-origin dependent transmission-ratio distortion is related to imprinting and possibly results from the loss of embryos which carry imprinted genes with imprinting marks that have been incorrectly reset. We analyzed transmission of alleles in four regions of the human genome that carry imprinted genes presumably critical for normal embryonic growth and development: 11p15.5 (H19, IGF2, HASH2, etc.), 11p13 (WT1), 7p11-12 (GRB10), and 6q25-q27 (IGF2R), among the offspring of 31 three-generation Centre d'Etude de polymorphism Humain (CEPH) families. Deviations from expected 1:1 ratios were found in the maternal chromosomes for regions 11p15.5, 11p13, and 6q25-27 and in the paternal chromosomes for regions 11p15 and 7p11-p12. The likelihood of the results was assessed empirically to be statistically significant (p = 0.0008), suggesting that the transmission ratios in the imprinted regions significantly deviated from 1:1. We did not find deviations from a 1:1 transmission ratio in imprinted regions that are not crucial for embryo viability (13q14 and 15q11-q13). The analysis of a larger set of 51 families for the 11p15.5 region suggests that there is heterogeneity among the families with regard to the transmission of 11p15.5 alleles. The results of this study are consistent with the hypothesis that grandparental-origin dependent transmission-ratio distortion is related to imprinting and embryo loss.

Design considerations for association studies of candidate genes in families

In genetic epidemiologic studies, investigators often use generalized linear models to evaluate the relationships between a disease trait and covariates, such as one or more candidate genes or an environmental exposure. Recently, attention has turned to study designs that mandate the inclusion of family members in addition to a proband. Standard models for analysis assume independent observations, which is unlikely to be true for family data, and the usual standard errors for the regression parameter estimates may be too large or too small, depending on the distribution of the covariates within and between families. The consequences of familial correlation on the study efficiency can be measured by a design effect that is equivalent to the relative information in a sample of unrelated individuals compared to a sample of families with the same number of individuals. We examine design effects for studies in association, and illustrate how the design effect is influenced by the intra-familial distribution of covariate values such as would be expected for a candidate gene. Typical design effects for a candidate gene range between 1.1 and 2.4, depending on the size of the family and the amount of unexplained familial correlation. These values correspond to a modest 10% increase in the required sample size up to more than doubling the requirements. Design effect values are useful in study design to compare the efficiency of studies that sample families versus independent individuals and to determine sample size requirements that account for familial correlation.

Racial differences in survival of patients on dialysis

BACKGROUND

Recent studies have documented racial differences in the crude mortality rates of patients on dialysis. However, proper interpretation of these findings requires adjustment for potential confounders and comorbid risk factors between the racial groups.

METHODS

We examined the clinical data on 3752 Caucasian patients, 451 Southeast Asian patients, 322 South Asian patients, and 319 black patients who were treated with hemodialysis or peritoneal dialysis under a Universal Health Care system in Toronto and prospectively followed between 1981 and 1995. In all patients, a number of comorbid risk factors for survival was assessed at the start of dialysis and was reassessed with their outcome status (that is, continued dialysis, transplantation, death, or loss to follow-up) at least every six months. Cox proportional hazards analysis was used to fit multivariate models predicting patient survival. Pairwise comparisons of the relative hazards of death between the racial groups were performed after stratifying for cardiovascular disease, diabetes mellitus, and hypertension at the start of dialysis, and were adjusted for differences in other comorbid risk factors.

RESULTS

The risk of death in Caucasian patients was significantly increased when compared with Southeast Asian patients, South Asian patients, and black patients [multivariate relative hazards (95% CI): 1.63 (1.36 to 1.97), 1.36 (1.07 to 1.73), 1.34 (1.07 to 1.67), respectively]. Additionally, we detected an interaction between race and cigarette smoking (P < 0. 004), suggesting that in the dialysis patients who smoked, whites had a higher mortality risk compared with non-whites.

CONCLUSIONS

Differences in patient survival on dialysis exist between racial groups. However, the genetic and environmental determinants that underlie these differences are presently unknown.

Incorporation of covariates into genome scanning using sib-pair analysis in bipolar affective disorder

Assessing heterogeneity in affected relative pair linkage analysis can help control type I error or identify important subgroups. We develop a method to incorporate covariates into sib-pair analysis, and hence are able to test for covariate effects on allele sharing in sib pairs. We propose a way of combining the five bipolar data sets to do a joint analysis of chromosome 18 data using this new method. Our results from a limited set of analyses do not show significant heterogeneity, and do not confirm the linkage previously identified on chromosome 18.

The impact of transmission-ratio distortion on allele sharing in affected sibling pairs

There have been recent reports of transmission-ratio distortion (TRD) or segregation distortion in families not selected for genetic disease. If TRD exists but is ignored, linkage studies searching for disease genes in affected relatives may be misinterpreted. We show that the identical-by-descent sharing patterns for affected sib pairs are strongly affected by TRD and, further, that the estimated statistical significance of a sib-pair linkage study may be extremely biased. However, we also show that, if TRD is suspected during the planning stage of a study, the planned sample size of the study needs to be increased by only a small amount to maintain the desired power.

Validation of linkage by sampling based on environmental exposures

After detecting linkage in one sample, most researchers will attempt to validate this finding in another sample. Three strategies for validating a primary linkage were compared, with a focus on methods that might be appropriate in the presence of gene x environment interaction. First, a validation sample was collected and analyzed using the same ascertainment procedure and methods as the primary sample. Second, a sample of families with particular exposure patterns were ascertained subsequent to a significant test for heterogeneity due to the exposure in the primary sample. A third strategy ascertained by exposure status when exposure-defined subgroup tests were significant in the primary sample. The second strategy reduced the number of false positive linkage signals identified through exposure subgroup identification (i.e., the third strategy), but in this GAW11 data that contained no qualitative gene x environment interactions, it had poor sensitivity. Power to detect heterogeneity depends on the differences in risk between exposed and unexposed.

Statistical issues in a metaregression analysis of randomized trials: impact on the dietary sodium intake and blood pressure relationship

In a meta-analysis of randomized trials of the effects of dietary sodium interventions on blood pressure, we found substantial heterogeneity among the studies. We were interested in evaluating whether measurement error, known to be a problem for dietary sodium measures, publication bias, or confounding factors could be responsible for the heterogeneity. A measurement error correction was developed that corrects both the slope and the intercept and takes into account the sample size of each study and the number of measurements taken on an individual. The measurement error correction had a minimal effect on the estimates, although it performed well in simulated data. A smoothed scatter plot was used to assess publication bias. Metaregressions provide a convenient way to jointly assess the effects of several factors, but care must be taken to fit an appropriate model.

Analysis of affected sib pairs, with covariates--with and without constraints

Covariate models have previously been developed as an extension to affected-sib-pair methods in which the covariate effects are jointly estimated with the degree of excess allele sharing. These models can estimate the differences in sib-pair allele sharing that are associated with measurable environment or genes. When there are no covariates, the pattern of identical-by-descent allele sharing in affected sib pairs is expected to fall within a small triangular region of the potential parameter space, under most genetic models. By restriction of the estimated allele sharing to this triangle, improved power is obtained in tests for genetic linkage. When the affected-sib-pair model is generalized to allow for covariates that affect allele sharing, however, new constraints and new methods for the application of constraints are required. Three generalized constraint methods are proposed and evaluated by use of simulated data. The results compare the power of the different methods, with and without covariates, for a single-gene model with age-dependent onset and for quantitative and qualitative gene-environment and gene-gene interaction models. Covariates can improve the power to detect linkage and can be particularly valuable when there are qualitative gene-environment interactions. In most situations, the best strategy is to assume that there is no dominance variance and to obtain constrained estimates for covariate models under this assumption.

Jackknife bias reduction for polychotomous logistic regression

Despite theoretical and empirical evidence that the usual MLEs can be misleading in finite samples and some evidence that bias reduced estimates are less biased and more efficient, they have not seen a wide application in practice. One can obtain bias reduced estimates by jackknife methods, with or without full iteration, or by use of higher order terms in a Taylor series expansion of the log-likelihood to approximate asymptotic bias. We provide details of these methods for polychotomous logistic regression with a nominal categorical response. We conducted a Monte Carlo comparison of the jackknife and Taylor series estimates in moderate sample sizes in a general logistic regression setting, to investigate dichotomous and trichotomous responses and a mixture of correlated and uncorrelated binary and normal covariates. We found an approximate two-step jackknife and the Taylor series methods useful when the ratio of the number of observations to the number of parameters is greater than 15, but we cannot recommend the two-step and the fully iterated jackknife estimates when this ratio is less than 20, especially when there are large effects, binary covariates, or multicollinearity in the covariates.

Validation of a predictive model of idiopathic membranous nephropathy: its clinical and research implications

Although a number of factors have consistently correlated with progression to chronic renal insufficiency (CRI) in idiopathic membranous glomerulonephropathy (IMGN), they appear late, are not quantitative in nature and have not been validated. We have determined that the highest sustained six-month period of proteinuria is an important predictor of progression. Using multiple logistic modelling, the only additional prognostic variables of importance in 184 Canadian patients were the initial creatinine clearance and the rate of change in function over this six-month interval. Independent data from Italy (101 patients) and Finland (78 patients) were obtained for comparison. Sensitivity, specificity, negative and positive predictive values and overall accuracy, as well as Pearson's goodness-of-fit and Harrell's "C" statistic were used to assess the fits of the model. Accuracy of prediction was > or = 85% in all three countries. Pearson's Chi-square goodness-of-fit showed good agreement across the spectrum and Harrell's "C" statistic was > or = 90%. Therefore, a predictive, semiquantitative algorithm in IMGN has been validated. Its relevance in patient management and in clinical trials is illustrated.

Effect of reduced dietary sodium on blood pressure: a meta-analysis of randomized controlled trials

OBJECTIVE

- To ascertain whether restriction of dietary sodium lowers blood pressure in hypertensive and normotensive individuals.

DATA SOURCES

- An English-language computerized literature search, restricted to human studies with Medical Subject Heading terms, "hypertension," "blood pressure," "vascular resistance," "sodium and dietary," "diet and sodium restricted," "sodium chloride," "clinical trial," "randomized controlled trial," and "prospective studies," was conducted. Bibliographies of review articles and personal files were also searched.

TRIAL SELECTION

- Trials that had randomized allocation to control and dietary sodium intervention groups, monitored by timed sodium excretion, with outcome measures of both systolic and diastolic blood pressure were selected by blinded review of the methods section.

DATA EXTRACTION

- Two observers extracted data independently, using purpose-designed forms, and discrepancies were resolved by discussion.

DATA SYNTHESIS

- The 56 trials that met our inclusion criteria showed significant heterogeneity. Publication bias was also evident. The mean reduction (95% confidence interval) in daily urinary sodium excretion, a proxy measure of dietary sodium intake, was 95 mmol/d (71-119 mmol/d) in 28 trials with 1131 hypertensive subjects and 125 mmol/d (95-156 mmol/d) in 28 trials with 2374 normotensive subjects. After adjustment for measurement error of urinary sodium excretion, the decrease in blood pressure for a 100-mmol/d reduction in daily sodium excretion was 3.7 mm Hg (2.35-5.05 mm Hg) for systolic (P<.001) and 0.9 mm Hg (-0.13 to 1.85 mm Hg) for diastolic (P=.09) in the hypertensive trials, and 1.0 mm Hg (0.51-1.56 mm Hg) for systolic (P<.001) and 0.1 mm Hg (-0.32 to 0.51 mm Hg) for diastolic (P=.64) in the normotensive trials. Decreases in blood pressure were larger in trials of older hypertensive individuals and small and nonsignificant in trials of normotensive individuals whose meals were prepared and who lived outside the institutional setting.

CONCLUSION

- Dietary sodium restriction for older hypertensive individuals might be considered, but the evidence in the normotensive population does not support current recommendations for universal dietary sodium restriction.

Evaluation of genetic and environmental effects using GEE and APM methods

Two analytic methods were used in the Problem 2 data set. First, generalized estimating equations (GEE) modelling was developed to adjust for familial correlation in regressions evaluating candidate genes and an environmental factor. Second, the affected-pedigree-member (APM) method was used to identify chromosomal regions of interest and linkage of candidate genes with disease affection status. The GEE method identified C5 (MG1) as important for the quantitative trait Q1 and the corresponding affection status DIS, but the APM method was only suggestive. The GEE method identified C2 (MG2) as important for Q2 but only marginally important for Q1 and not important for DIS.