ABCB1 (MDR1) predicts remission on P-gp substrates in chronic depression.

The hypothesis that allelic variation in the multidrug resistance-1 (MDR1 or ABCB1) gene encoding the P-glycoprotein (P-gp) blood-brain barrier efflux pump is associated with remission and side effects was tested in chronic major depression patients treated with P-gp substrates. In 83 patients from the REVAMP trial, frequency of and time to remission as well as side effects was tested among genotype groups at 6 ABCB1 single nucleotide polymorphisms (SNPs). These six SNPs are significantly associated with remission and time to remission, with minor allele carriers on rs2235040 and rs9282564 attaining statistical significance after controlling for the other ABCB1 SNPs. The six ABCB1 SNPs are also significantly associated with the average side effects. However, here common homozygotes on rs2235040 and rs9282564 demonstrated significantly higher side effects after controlling for the effects of the other ABCB1 SNPs. These findings confirm and extend previous observations that minor alleles of two ABCB1 SNPs predict remission to treatment with substrates and demonstrate that common homozygotes on these SNPs experience greater side effects. Results point to the potential importance of ABCB1 variation for personalized medicine approaches to treating depression.

P-values in genomics: apparent precision masks high uncertainty.

Scientists often interpret P-values as measures of the relative strength of statistical findings. This is common practice in large-scale genomic studies where P-values are used to choose which of numerous hypothesis test results should be pursued in subsequent research. In this study, we examine P-value variability to assess the degree of certainty P-values provide. We develop prediction intervals for the P-value in a replication study given the P-value observed in an initial study. The intervals depend on the initial value of P and the ratio of sample sizes between the initial and replication studies, but not on the underlying effect size or initial sample size. The intervals are valid for most large-sample statistical tests in any context, and can be used in the presence of single or multiple tests. While P-values are highly variable, future P-value variability can be explicitly predicted based on a P-value from an initial study. The relative size of the replication and initial study is an important predictor of the P-value in a subsequent replication study. We provide a handy calculator implementing these results and apply them to a study of Alzheimer's disease and recent findings of the Cross-Disorder Group of the Psychiatric Genomics Consortium. This study suggests that overinterpretation of very significant, but highly variable, P-values is an important factor contributing to the unexpectedly high incidence of non-replication. Formal prediction intervals can also provide realistic interpretations and comparisons of P-values associated with different estimated effect sizes and sample sizes.

HPA axis genetic variation, cortisol and psychosis in major depression.

Genetic variation underlying hypothalamic pituitary adrenal (HPA) axis overactivity in healthy controls (HCs) and patients with severe forms of major depression has not been well explored, but could explain risk for cortisol dysregulation. In total, 95 participants were studied: 40 patients with psychotic major depression (PMD); 26 patients with non-psychotic major depression (NPMD); and 29 HCs. Collection of genetic material was added one third of the way into a larger study on cortisol, cognition and psychosis in major depression. Subjects were assessed using the Brief Psychiatric Rating Scale, the Hamilton Depression Rating Scale and the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders. Blood was collected hourly for determination of cortisol from 1800 to 0900 h and for the assessment of alleles for six genes involved in HPA axis regulation. Two of the six genes contributed significantly to cortisol levels, psychosis measures or depression severity. After accounting for age, depression and psychosis, and medication status, only allelic variation for the glucocorticoid receptor (GR) gene accounted for a significant variance for mean cortisol levels from 1800 to 0100 h (r(2)=0.288) and from 0100 to 0900 h (r(2)=0.171). In addition, GR and corticotropin-releasing hormone receptor 1 (CRHR1) genotypes contributed significantly to psychosis measures and CRHR1 contributed significantly to depression severity rating.

The cost of large numbers of hypothesis tests on power, effect size and sample size.

Advances in high-throughput biology and computer science are driving an exponential increase in the number of hypothesis tests in genomics and other scientific disciplines. Studies using current genotyping platforms frequently include a million or more tests. In addition to the monetary cost, this increase imposes a statistical cost owing to the multiple testing corrections needed to avoid large numbers of false-positive results. To safeguard against the resulting loss of power, some have suggested sample sizes on the order of tens of thousands that can be impractical for many diseases or may lower the quality of phenotypic measurements. This study examines the relationship between the number of tests on the one hand and power, detectable effect size or required sample size on the other. We show that once the number of tests is large, power can be maintained at a constant level, with comparatively small increases in the effect size or sample size. For example at the 0.05 significance level, a 13% increase in sample size is needed to maintain 80% power for ten million tests compared with one million tests, whereas a 70% increase in sample size is needed for 10 tests compared with a single test. Relative costs are less when measured by increases in the detectable effect size. We provide an interactive Excel calculator to compute power, effect size or sample size when comparing study designs or genome platforms involving different numbers of hypothesis tests. The results are reassuring in an era of extreme multiple testing.

A randomized trial of computer-based reminders and audit and feedback to improve HIV screening in a primary care setting.

Despite recommendations for voluntary HIV screening, few medical centres have implemented screening programmes. The objective of the study was to determine whether an intervention with computer-based reminders and feedback would increase screening for HIV in a Department of Veterans Affairs (VA) health-care system. The design of the study was a randomized controlled trial at five primary care clinics at the VA Palo Alto Health Care System. All primary care providers were eligible to participate in the study. The study intervention was computer-based reminders to either assess HIV risk behaviours or to offer HIV testing; feedback on adherence to reminders was provided. The main outcome measure was the difference in HIV testing rates between intervention and control group providers. The control group providers tested 1.0% (n = 67) and 1.4% (n = 106) of patients in the preintervention and intervention period, respectively; intervention providers tested 1.8% (n = 98) and 1.9% (n = 114), respectively (P = 0.75). In our random sample of 753 untested patients, 204 (27%) had documented risk behaviours. Providers were more likely to adhere to reminders to test rather than with reminders to perform risk assessment (11% versus 5%, P < 0.01). Sixty-one percent of providers felt that lack of time prevented risk assessment. In conclusion, in primary care clinics in our setting, HIV testing rates were low. Providers were unaware of the high rates of risky behaviour in their patient population and perceived important barriers to testing. Low-intensity clinical reminders and feedback did not increase rates of screening.

A chronology of fine-scale gene mapping by linkage disequilibrium.

The past decade produced several proposals for fine-scale gene mapping using linkage disequilibrium data. The suggested methods fall into two main groups, those that rely on pairwise statistics and those that rely on haplotypes. This paper reviews each strategy's development from a chronological perspective.

Linkage disequilibrium and gene mapping: an empirical least-squares approach.

This paper proposes a novel approach for fine-scale mapping of disease genes that is based on the well-known linkage-disequilibrium parameter delta. Using a very simple, very general model, I show how delta can be interpreted in terms of identity-by-descent probabilities. The value of delta follows a piecewise curve along the chromosome, with the maximum occurring at the disease locus where the two pieces intersect. A semiparametric, multilocus approach is used to fit this nonlinear regression curve in order to estimate the gene location. Using the bootstrap to empirically estimate much of the probability model from the data avoids the need for many detailed population assumptions. One advantage of the approach is its use of the observed covariance structure of the data, which can be highly informative as to the gene location. I illustrate the method on the cystic fibrosis data of Kerem et al.

A conditional inference framework for extending the transmission/disequilibrium test.

The transmission/disequilibrium test (TDT) of Terwilliger and Ott [Hum Hered 1992;42:337-346] and Spielman et al. [Am J Hum Genet 1993;52:506-516] is widely used to detect linkage and/or association between a genetically influenced disease and the alleles of a codominant marker locus. The TDT was specifically designed to avoid the spurious population associations produced by ethnic stratification of a sample of affected people. In this paper, we describe permutation extensions of the TDT that share this advantage. Our conditional inference framework permits extensions to multiple alleles, multiple loci, unaffected siblings, and genotypic rather than allelic associations. In the case of multiple loci, the conditional perspective provides a straightforward correction for multiple tests that can be substantially more powerful than the standard Bonferroni correction.

Multipoint mapping calculations for sperm-typing data.

This paper explains how multipoint likelihoods can be computed for sperm-typing data. Experimental errors such as multiple sperm per tube, inadequate amplification, and contamination by exogenous DNA are explicitly taken into account. By limiting the number of sperm theoretically possible per tube to a predetermined maximum and by assuming no chiasma interference, maximum-likelihood estimation can be carried out rapidly using the theory of hidden Markov chains.

Multipoint linkage map of the human pseudoautosomal region, based on single-sperm typing: do double crossovers occur during male meiosis?

Sperm typing was used to measure recombination fractions among pseudoautosomal markers and the beginning of the X/Y-specific sequences located at the pseudoautosomal boundary. These experiments included primer-extension preamplification and PCR followed by allele typing using gel electrophoresis. A newly developed data-analysis program allowed the construction of the first multipoint-linkage sperm-typing map, using results obtained on seven loci from three individuals. The large sample size not only confirmed the increased recombination activity of the pseudoautosomal region but allowed an estimate of interference of recombination to be made. The coefficient of coincidence was calculated to be .26 over a physical distance of only approximately 1,800 kb. The observation of a few sperm presumably resulting from double recombination argues that more than one crossover event can occur in this region during male meiosis.

In vivo sequence diversity of the protease of human immunodeficiency virus type 1: presence of protease inhibitor-resistant variants in untreated subjects.

We have evaluated the sequence diversity of the protease human immunodeficiency virus type 1 in vivo. Our analysis of 246 protease coding domain sequences obtained from 12 subjects indicates that amino acid substitutions predicted to give rise to protease inhibitor resistance may be present in patients who have not received protease inhibitors. In addition, we demonstrated that amino acid residues directly involved in enzyme-substrate interactions may be varied in infected individuals. Several of these substitutions occurred in combination either more or less frequently than would be expected if their appearance was independent, suggesting that one substitution may compensate for the effects of another. Taken together, our analysis indicates that the human immunodeficiency virus type 1 protease has flexibility sufficient to vary critical subsites in vivo, thereby retaining enzyme function and viral pathogenicity.