Pharmacogenetic assessment of tafenoquine efficacy in patients with Plasmodium vivax malaria.

Plasmodium vivax has the largest geographic range of human malaria species and is challenging to manage and eradicate due to its ability to establish a dormant liver stage, the hypnozoite, which can reactivate leading to relapse. Until recently, the only treatment approved to kill hypnozoites was the 8-aminoquinoline, primaquine, requiring daily treatment for 14 days. Tafenoquine, an 8-aminoquinoline single-dose treatment with activity against P. vivax hypnozoites, has recently been approved by the US Food and Drug Administration and Australian Therapeutic Goods Administration for the radical cure of P. vivax malaria in patients 16 years and older. We conducted an exploratory pharmacogenetic analysis (GSK Study 208099) to assess the role of host genome-wide variation on tafenoquine efficacy in patients with P. vivax malaria using data from three GSK clinical trials, GATHER and DETECTIVE Part 1 and Part 2. Recurrence-free efficacy at 6 and 4 months and time to recurrence up to 6 months postdosing were analyzed in 438 P. vivax malaria patients treated with tafenoquine. Among the approximately 10.6 million host genetic variants analyzed, two signals reached genome-wide significance (P value ≤ 5 × 10). rs62103056, and variants in a chromosome 12 intergenic region, were associated with recurrence-free efficacy at 6 and 4 months, respectively. Neither of the signals has an obvious biological rationale and would need replication in an independent population. This is the first genome-wide association study to evaluate genetic influence on response to tafenoquine in P. vivax malaria.

Pharmacogenetic analysis of belimumab fails to identify robust genetic predictors of efficacy in lupus.

GlaxoSmithKline (GSK) conducted pharmacogenetic (PGx) analyses to determine whether genetic variants influence response to belimumab treatment in patients with systemic lupus erythematosus (SLE). We conducted an exploratory genome-wide meta-analysis (GWAS) of 10.9 million genetic variants and the efficacy data from 816 belimumab-treated SLE patients in three phase 3 belimumab clinical studies. Two highly correlated variants, rs293983 and rs364370, in the ANO3 (anoctamin 3) gene region were significantly associated with efficacy as measured by the SLE Response Index (SRI4) with a per-T-allele odds ratio (OR) of 2.15 [95% confidence interval (CI): 1.66-2.79, P=8.0×10]. In contrast, there was no association with SRI4 response in 577 placebo-treated patients (per-T-allele OR: 0.98; 95% CI: 0.74-1.29, P=0.87). A post-hoc analysis by geographic region revealed a strong SRI4 response signal in 157 belimumab-treated patients from Asia (per-T-allele OR=2.85, 95% CI: 1.41-5.74, P=0.0021). On the basis of this encouraging finding in Asian patients, we conducted a confirmatory analysis of the SRI4 end point in an independent phase 3 study of SLE patients from northeast Asia. We found no evidence of an association between rs293983 and SRI4 response in 204 belimumab-treated patients (per-T-allele OR: 0.90, 95% CI: 0.52-1.57, P=0.64). The inability to replicate the observed GWAS effect suggests this was a false positive result; hence, we failed to identify any genetic variants significantly associated with belimumab efficacy.

Tafenoquine treatment of Plasmodium vivax malaria: suggestive evidence that CYP2D6 reduced metabolism is not associated with relapse in the Phase 2b DETECTIVE trial.

BACKGROUND: Tafenoquine (TQ) and primaquine (PQ) are 8-aminoquinolines (8-AQ) with anti-hypnozoite activity against vivax malaria. PQ is the only FDA-approved medicine for preventing relapsing Plasmodium vivax infection and TQ is currently in phase 3 clinical trials for the same indication. Recent studies have provided evidence that cytochrome P450 (CYP) metabolism via CYP2D6 plays a role in PQ efficacy against P. vivax and have suggested that this effect may extend to other 8-AQs, including TQ. Here, a retrospective pharmacogenetic (PGx) investigation was performed to assess the impact of CYP2D6 metabolism on TQ and PQ efficacy in the treatment of P. vivax in the DETECTIVE study (TAF112582), a recently completed, randomized, phase 2b dose-ranging clinical trial. The impact of CYP2D6 on TQ pharmacokinetics (PK) was also investigated in TAF112582 TQ-treated subjects and in vitro CYP metabolism of TQ was explored. A limitation of the current study is that TAF112582 was not designed to be well powered for PGx, thus our findings are based on TQ or PQ efficacy in CYP2D6 intermediate metabolizers (IM), as there were insufficient poor metabolizers (PM) to draw any conclusion on the impact of the PM phenotype on efficacy. METHODS: The impact of genetically-predicted CYP2D6 reduced metabolism on relapse-free efficacy six months post-dosing of TQ or PQ, both administered in conjunction with chloroquine (CQ), was assessed using exact statistical methods in 198 P. vivax-infected study participants comparing IM to extensive metabolizers (EM). The influence of CYP2D6 metabolizer phenotypes on TQ PK was assessed comparing median TQ area under the curve (AUC). In vitro metabolism of TQ was investigated using recombinant, over-expressed human CYP enzymes and human hepatocytes. Metabolite identification experiments were performed using liquid chromatography-mass spectrometry. RESULTS: Reduction of CYP2D6 activity was not associated with an increase in relapse-rate in TQ-treated subjects (p = 0.57). In contrast, and in accordance with recent literature, CYP2D6 IMs were more common (p = 0.05) in PQ-treated subjects who relapsed (50 %) than in subjects who remained relapse-free (17 %). Further, CYP2D6 metabolizer phenotypes had no significant effect on TQ AUC, and only minimal metabolism of TQ could be detected in hepatic in vitro systems. CONCLUSION: Together, these data provide preliminary evidence that in CYP2D6 IMs, TQ efficacy in P. vivax-infected individuals is not diminished to the same extent as PQ. As there were no PMs in either the TQ or PQ treatment arms of TAF112582, no conclusions could be drawn on potential differences in PMs. These findings suggest that differential effects of CYP2D6 metabolism on TQ and PQ efficacy could be a differentiation factor between these 8-AQs, but results remain to be confirmed prospectively in the ongoing phase 3 studies.

Analysis of rare variant population structure in Europeans explains differential stratification of gene-based tests.

There is substantial interest in the role of rare genetic variants in the etiology of complex human diseases. Several gene-based tests have been developed to simultaneously analyze multiple rare variants for association with phenotypic traits. The tests can largely be partitioned into two classes - 'burden' tests and 'joint' tests - based on how they accumulate evidence of association across sites. We used the empirical joint site frequency spectra of rare, nonsynonymous variation from a large multi-population sequencing study to explore the effect of realistic rare variant population structure on gene-based tests. We observed an important difference between the two test classes: their susceptibility to population stratification. Focusing on European samples, we found that joint tests, which allow variants to have opposite directions of effect, consistently showed higher levels of P-value inflation than burden tests. We determined that the differential stratification was caused by two specific patterns in the interpopulation distribution of rare variants, each correlating with inflation in one of the test classes. The pattern that inflates joint tests is more prevalent in real data, explaining the higher levels of inflation in these tests. Furthermore, we show that the different sources of inflation between tests lead to heterogeneous responses to genomic control correction and the number of variants analyzed. Our results indicate that care must be taken when interpreting joint and burden analyses of the same set of rare variants, in particular, to avoid mistaking inflated P-values in joint tests for stronger signals of true associations.

The influence of genomic context on mutation patterns in the human genome inferred from rare variants.

Understanding patterns of spontaneous mutations is of fundamental interest in studies of human genome evolution and genetic disease. Here, we used extremely rare variants in humans to model the molecular spectrum of single-nucleotide mutations. Compared to common variants in humans and human-chimpanzee fixed differences (substitutions), rare variants, on average, arose more recently in the human lineage and are less affected by the potentially confounding effects of natural selection, population demographic history, and biased gene conversion. We analyzed variants obtained from a population-based sequencing study of 202 genes in >14,000 individuals. We observed considerable variability in the per-gene mutation rate, which was correlated with local GC content, but not recombination rate. Using >20,000 variants with a derived allele frequency ≤ 10(-4), we examined the effect of local GC content and recombination rate on individual variant subtypes and performed comparisons with common variants and substitutions. The influence of local GC content on rare variants differed from that on common variants or substitutions, and the differences varied by variant subtype. Furthermore, recombination rate and recombination hotspots have little effect on rare variants of any subtype, yet both have a relatively strong impact on multiple variant subtypes in common variants and substitutions. This observation is consistent with the effect of biased gene conversion or selection-dependent processes. Our results highlight the distinct biases inherent in the initial mutation patterns and subsequent evolutionary processes that affect segregating variants.

Deep sequencing of the LRRK2 gene in 14,002 individuals reveals evidence of purifying selection and independent origin of the p.Arg1628Pro mutation in Europe.

Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single-nucleotide variants, 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Among Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.

A genome-wide investigation of SNPs and CNVs in schizophrenia.

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater "load" of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens.

Candidate single-nucleotide polymorphisms from a genomewide association study of Alzheimer disease.

OBJECTIVE: To identify single-nucleotide polymorphisms (SNPs) associated with risk and age at onset of Alzheimer disease (AD) in a genomewide association study of 469 438 SNPs. DESIGN: Case-control study with replication. SETTING: Memory referral clinics in Canada and the United Kingdom. PARTICIPANTS: The hypothesis-generating data set consisted of 753 individuals with AD by National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer's Disease and Related Disorders Association criteria recruited from 9 memory referral clinics in Canada and 736 ethnically matched control subjects; control subjects were recruited from nonbiological relatives, friends, or spouses of the patients and did not exhibit cognitive impairment by history or cognitive testing. The follow-up data set consisted of 418 AD cases and 249 nondemented control cases from the United Kingdom Medical Research Council Genetic Resource for Late-Onset AD recruited from clinics at Cardiff University, Cardiff, Wales, and King's College London, London, England. MAIN OUTCOME MEASURES: Odds ratios and 95% confidence intervals for association of SNPs with AD by logistic regression adjusted for age, sex, education, study site, and French Canadian ancestry (for the Canadian data set). Hazard ratios and 95% confidence intervals from Cox proportional hazards regression for age at onset with similar covariate adjustments. RESULTS: Unadjusted, SNP RS4420638 within APOC1 was strongly associated with AD due entirely to linkage disequilibrium with APOE. In the multivariable adjusted analyses, 3 SNPs within the top 120 by P value in the logistic analysis and 1 in the Cox analysis of the Canadian data set provided additional evidence for association at P< .05 within the United Kingdom Medical Research Council data set: RS7019241 (GOLPH2), RS10868366 (GOLPH2), RS9886784 (chromosome 9), and RS10519262 (intergenic between ATP8B4 and SLC27A2). CONCLUSIONS: Our genomewide association analysis again identified the APOE linkage disequilibrium region as the strongest genetic risk factor for AD. This could be a consequence of the coevolution of more than 1 susceptibility allele, such as APOC1, in this region. We also provide new evidence for additional candidate genetic risk factors for AD that can be tested in further studies.

Use of whole-genome association scans in disease gene identification, drug discovery and development.

Over the past decade, whole-genome scans have been used by academia and industry as an increasingly important tool in identifying genes of disease susceptibility. Genome coverage has improved dramatically, from sparse panels of hundreds or thousands of genetic markers five to ten years ago, to panels now comprising over 500,000 markers that capture more than 80% of the genetic information in the genome. Whole-genome scans have played a role in drug discovery, for which knowledge of the genes and gene pathways involved in disease susceptibility can be incorporated into the selection of drug targets. Such scans also have an important role in drug development, as the pharmaceutical industry shifts from a blockbuster strategy to a niche market approach; given that not all patients will receive benefit from a particular medication, genetic markers that predict efficacy can be used to identify subgroups of patients who display a significant therapeutic response. Similarly, genetic information can be used during the drug development and postmarketing stages to predict individuals who are at risk for an adverse event. At-risk patients can receive alternative therapies, while those individuals who are not at risk, and benefit from a given medication, can continue on the treatment regimen. This feature article discusses the use of whole-genome association scans in disease gene identification, drug discovery and development.

Genome-wide and fine-mapping linkage studies of type 2 diabetes and glucose traits in the Old Order Amish: evidence for a new diabetes locus on chromosome 14q11 and confirmation of a locus on chromosome 1q21-q24.

We conducted a genome scan using a 10-cM map to search for genes linked to type 2 diabetes in 691 individuals from a founder population, the Old Order Amish. We then saturated two regions on chromosomes 1 and 14 showing promising linkage signals with additional markers to produce a approximately 2-cM map for fine mapping. Analyses of both discrete traits (type 2 diabetes and the composite trait of type 2 diabetes and/or impaired glucose homeostasis [IGH]), and quantitative traits (glucose levels during a 75-g oral glucose challenge, designated glucose 0-180 and HbA(1c)) were performed. We obtained significant evidence for linkage to type 2 diabetes in a novel region on chromosome 14q11 (logarithm of odds [LOD] for diabetes = 3.48, P = 0.00005). Furthermore, we observed evidence for the existence of a diabetes-related locus on chromosome 1q21-q24 (LOD for type 2 diabetes/IGH = 2.35, P = 0.0008), a region shown to be linked to diabetes in several other studies. Suggestive evidence for linkage to glucose traits was observed on three other regions: 14q11-q13 (telomeric to that above with LOD = 1.82-1.85 for glucose 150 and 180), 1p31 (LOD = 1.28-2.30 for type 2 diabetes and glucose 120-180), and 18p (LOD = 3.07, P = 0.000085 for HbA(1c) and LOD = 1.50 for glucose 0). In conclusion, our findings provide evidence that type 2 diabetes susceptibility genes reside on chromosomes 1, 14, and 18.

Eating behavior in the Old Order Amish: heritability analysis and a genome-wide linkage analysis.

BACKGROUND: Eating behavior and thus dietary intake affect the development of obesity-related diseases such as diabetes, hypertension, and hyperlipidemia. OBJECTIVE: We investigated the genetic underpinnings of eating behavior. DESIGN: We administered a standardized eating behavior inventory to 624 adults from 28 families participating in the Amish Family Diabetes Study. Three quantifiable components of eating behavior were measured: restraint, disinhibition, and hunger. Associations between eating behavior scores and physical characteristics were evaluated. Heritability analysis and a genome-wide multipoint linkage analysis were performed. RESULTS: Eating behavior scores were associated with obesity and obesity-related phenotypes. Heritability estimates were 0.28 +/- 0.09 for restraint, 0.40 +/- 0.10 for disinhibition, and 0.23 +/- 0.09 for hunger (P < 0.001). The linkage analysis showed 4 regions of suggestive linkage. We observed suggestive evidence for linkage of restraint scores to 2 chromosomal regions, near markers D3S1304 [LOD (log of odds) = 2.5, P = 0.0003] and D6S276 (LOD = 2.3, P = 0.0006). We previously reported that D3S1304 is linked to a locus influencing percentage body fat in this same population (LOD = 1.6), suggesting that this behavioral phenotype may be secondary to obesity. The maximum LOD scores for disinhibition were 1.6 (P = 0.003) near marker D7S657 and 1.4 (P = 0.005) near marker D16S752. The maximum LOD score for hunger was 1.4 (P = 0.005) near marker D3S1278. CONCLUSION: Significant familial effects on eating behavior and suggestive genetic linkage were found in Amish adults.