Multivariate analysis of a missense variant in CREBRF reveals associations with measures of adiposity in people of Polynesian ancestries.

The minor allele of rs373863828, a missense variant in CREB3 Regulatory Factor, is associated with several cardiometabolic phenotypes in Polynesian peoples. To better understand the variant, we tested the association of rs373863828 with a panel of correlated phenotypes (body mass index [BMI], weight, height, HDL cholesterol, triglycerides, and total cholesterol) using multivariate Bayesian association and network analyses in a Samoa cohort (n = 1632), Aotearoa New Zealand cohort (n = 1419), and combined cohort (n = 2976). An expanded set of phenotypes (adding estimated fat and fat-free mass, abdominal circumference, hip circumference, and abdominal-hip ratio) was tested in the Samoa cohort (n = 1496). In the Samoa cohort, we observed significant associations (log10 Bayes Factor [BF] ≥ 5.0) between rs373863828 and the overall phenotype panel (8.81), weight (8.30), and BMI (6.42). In the Aotearoa New Zealand cohort, we observed suggestive associations (1.5 < log10 BF < 5) between rs373863828 and the overall phenotype panel (4.60), weight (3.27), and BMI (1.80). In the combined cohort, we observed concordant signals with larger log10 BFs. In the Samoa-specific expanded phenotype analyses, we also observed significant associations between rs373863828 and fat mass (5.65), abdominal circumference (5.34), and hip circumference (5.09). Bayesian networks provided evidence for a direct association of rs373863828 with weight and indirect associations with height and BMI.

dbGaPCheckup: pre-submission checks of dbGaP-formatted subject phenotype files.

BACKGROUND: Data archiving and distribution are essential to scientific rigor and reproducibility of research. The National Center for Biotechnology Information's Database of Genotypes and Phenotypes (dbGaP) is a public repository for scientific data sharing. To support curation of thousands of complex data sets, dbGaP has detailed submission instructions that investigators must follow when archiving their data. RESULTS: We developed dbGaPCheckup, an R package which implements a series of check, awareness, reporting, and utility functions to support data integrity and proper formatting of the subject phenotype data set and data dictionary prior to dbGaP submission. For example, as a tool, dbGaPCheckup ensures that the data dictionary contains all fields required by dbGaP, and additional fields required by dbGaPCheckup; the number and names of variables match between the data set and data dictionary; there are no duplicated variable names or descriptions; observed data values are not more extreme than the logical minimum and maximum values stated in the data dictionary; and more. The package also includes functions that implement a series of minor/scalable fixes when errors are detected (e.g., a function to reorder the variables in the data dictionary to match the order listed in the data set). Finally, we also include reporting functions that produce graphical and textual descriptives of the data to further reduce the likelihood of data integrity issues. The dbGaPCheckup R package is available on CRAN ( https://CRAN.R-project.org/package=dbGaPCheckup ) and developed on GitHub ( https://github.com/lwheinsberg/dbGaPCheckup ). CONCLUSION: dbGaPCheckup is an innovative assistive and timesaving tool that fills an important gap for researchers by making dbGaP submission of large and complex data sets less error prone.

Post hoc power is not informative.

Post hoc power estimates are often requested by reviewers and/or performed by researchers after a study has been conducted. The purpose of this commentary is to provide a heuristic explanation of why post hoc power should not be used. To illustrate our point, we provide a detailed simulation study of two essentially identical research experiments hypothetically conducted in parallel at two separate universities. The simulation demonstrates that post hoc power calculations are misleading and simply not informative for data interpretation. As such, we encourage authors and peer-reviewers to avoid using or requesting post hoc power calculations.

Association of rs9939609 in FTO with BMI among Polynesian peoples living in Aotearoa New Zealand and other Pacific nations.

The fat mass and obesity associated (FTO) locus consistently associates with higher body mass index (BMI) across diverse ancestral groups. However, previous small studies of people of Polynesian ancestries have failed to replicate the association. In this study, we used Bayesian meta-analysis to test rs9939609, the most replicated FTO variant, for association with BMI with a large sample (n = 6095) of Aotearoa New Zealanders of Polynesian (Maori and Pacific) ancestry and of Samoan people living in the Independent State of Samoa and in American Samoa. We did not observe statistically significant association within each separate Polynesian subgroup. Bayesian meta-analysis of the Aotearoa New Zealand Polynesian and Samoan samples resulted in a posterior mean effect size estimate of +0.21 kg/m2, with a 95% credible interval [+0.03 kg/m2, +0.39 kg/m2]. While the Bayes Factor (BF) of 0.77 weakly favors the null, the BF = 1.4 Bayesian support interval is [+0.04, +0.20]. These results suggest that rs9939609 in FTO may have a similar effect on mean BMI in people of Polynesian ancestries as previously observed in other ancestral groups.

Validity of anthropometric equation-based estimators of fat mass in Samoan adults.

INTRODUCTION: In 1999, a set of highly accurate Polynesian-specific equations to estimate adult body fat from non-invasive field measures of age, sex, height, and weight (Equation 1), age, sex, height, weight, and bioelectrical impedance analysis (BIA) resistance (Equation 2), and age, sex, height, weight, and the sum of two skinfold thicknesses (Equation 3) were published. The purpose of this study was to evaluate the performance of the equation-based estimators in a sample of Samoan adults recruited 20 years later between 2017 and 2019. METHODS: Age, sex, height, weight, BIA resistance, skinfold thickness, and fat mass as measured using dual energy x-ray absorptiometry (DXA) were available for 432 Samoan adults (mean age 50.9 years, 56% female) seen in 2017/2019. We compared equation-derived fat mass and DXA-derived fat mass using scatterplots and Pearson correlation coefficients. We then updated the equation coefficient estimates in a training set (2/3 of the sample) and evaluated the performance of the updated equations in a testing set (the remaining 1/3 of the sample). RESULTS: Equation-derived fat mass was strongly correlated with DXA-derived fat mass for Equation (1) (r2  = 0.95, n = 432), Equation (2) (r2  = 0.97, n = 425), and Equation (3) (r2  = 0.95, n = 426). Updating the equation coefficient estimates resulted in mostly similar coefficients and nearly identical testing set performance for Equation (1) (r2  = 0.96, n = 153), Equation (2) (r2  = 0.98, n = 150), and Equation (3) (r2  = 0.96, n = 150). CONCLUSIONS: The Polynesian-specific body fat estimation equations remained stable despite changing social and environmental factors and marked increase in obesity prevalence in Samoa.

Evolutionary history of modern Samoans.

Archaeological studies estimate the initial settlement of Samoa at 2,750 to 2,880 y ago and identify only limited settlement and human modification to the landscape until about 1,000 to 1,500 y ago. At this point, a complex history of migration is thought to have begun with the arrival of people sharing ancestry with Near Oceanic groups (i.e., Austronesian-speaking and Papuan-speaking groups), and was then followed by the arrival of non-Oceanic groups during European colonialism. However, the specifics of this peopling are not entirely clear from the archaeological and anthropological records, and is therefore a focus of continued debate. To shed additional light on the Samoan population history that this peopling reflects, we employ a population genetic approach to analyze 1,197 Samoan high-coverage whole genomes. We identify population splits between the major Samoan islands and detect asymmetrical gene flow to the capital city. We also find an extreme bottleneck until about 1,000 y ago, which is followed by distinct expansions across the islands and subsequent bottlenecks consistent with European colonization. These results provide for an increased understanding of Samoan population history and the dynamics that inform it, and also demonstrate how rapid demographic processes can shape modern genomes.

CHIT: an allele-specific method for testing the association between molecular quantitative traits and phenotype-genotype interaction.

MOTIVATION: Allele-specific differences in molecular traits can be obtained from next-generation sequencing data and could potentially improve testing power, but such information is usually overlooked in association studies. Furthermore, the variation of molecular quantitative traits (e.g. gene expression) could result from the interaction effect of genotypes and phenotypes, but it is challenging to identify such interaction signals in complex disease studies in humans due to small genetic effect sizes and/or small sample sizes. RESULTS: We develop a novel statistical method, the combined haplotype interaction test (CHIT), which tests for association between molecular quantitative traits and phenotype-genotype interactions by modeling the total read counts and allele-specific reads in a target region. CHIT can be used as a supplementary analysis to the regular linear interaction regression. In our simulations, CHIT obtains non-inflated type I error rates, and it has higher power than a standard interaction quantitative trait locus approach based on linear regression models. Finally, we illustrate CHIT by testing associations between gene expression obtained by RNA-seq and the interaction of SNPs and atopy status from a study of childhood asthma in Puerto Ricans, and results demonstrate that CHIT could be more powerful than a standard linear interaction expression quantitative trait loci approach. AVAILABILITY AND IMPLEMENTATION: The CHIT algorithm has been implemented in Python. The source code and documentation are available and can be downloaded from https://github.com/QiYanPitt/CHIT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Decreased DNA Methylation of RGMA is Associated with Intracranial Hypertension After Severe Traumatic Brain Injury: An Exploratory Epigenome-Wide Association Study.

BACKGROUND: Cerebral edema and intracranial hypertension are major contributors to unfavorable prognosis in traumatic brain injury (TBI). Local epigenetic changes, particularly in DNA methylation, may influence gene expression and thus host response/secondary injury after TBI. It remains unknown whether DNA methylation in the central nervous system is associated with cerebral edema severity or intracranial hypertension post TBI. We sought to identify epigenome-wide DNA methylation patterns associated with these forms of secondary injury after TBI. METHODS: We obtained genome-wide DNA methylation profiles of DNA extracted from ventricular cerebrospinal fluid samples at three different postinjury time points from a prospective cohort of patients with severe TBI (n = 89 patients, 254 samples). Cerebral edema and intracranial pressure (ICP) measures were clustered to generate composite end points of cerebral edema and ICP severity. We performed an unbiased epigenome-wide association study (EWAS) to test associations between DNA methylation at 419,895 cytosine-phosphate-guanine (CpG) sites and cerebral edema/ICP severity categories. Given inflated p values, we conducted permutation tests for top CpG sites to filter out potential false discoveries. RESULTS: Our data-driven hierarchical clustering across six cerebral edema and ICP measures identified two groups differing significantly in ICP based on the EWAS-identified CpG site cg22111818 in RGMA (Repulsive guidance molecule A, permutation p = 4.20 × 10-8). At 3-4 days post TBI, patients with severe intracranial hypertension had significantly lower levels of methylation at cg22111818. CONCLUSIONS: We report a novel potential relationship between intracranial hypertension after TBI and an acute, nonsustained reduction in DNA methylation at cg22111818 in the RGMA gene. To our knowledge, this is the largest EWAS in severe TBI. Our findings are further strengthened by previous findings that RGMA modulates axonal repair in other central nervous system disorders, but a role in intracranial hypertension or TBI has not been previously identified. Additional work is warranted to validate and extend these findings, including assessment of its possible role in risk stratification, identification of novel druggable targets, and ultimately our ability to personalize therapy in TBI.

Genome-wide association studies in Samoans give insight into the genetic architecture of fasting serum lipid levels.

The current understanding of the genetic architecture of lipids has largely come from genome-wide association studies (GWAS). To date, few GWAS have examined the genetic architecture of lipids in Polynesians, and none have in Samoans, whose unique population history, including many population bottlenecks, may provide insight into the biological foundations of variation in lipid levels. Here we performed a GWAS of four fasting serum lipid levels: total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides (TG) in a sample of 2849 Samoans, with validation genotyping for associations in a replication cohort comprising 1798 Samoans and American Samoans. We identified multiple genome-wide significant associations (P < 5 × 10-8) previously seen in other populations-APOA1 with TG, CETP with HDL, and APOE with TC and LDL-and several suggestive associations (P < 1 × 10-5), including an association of variants downstream of MGAT1 and RAB21 with HDL. However, we observed different association signals for variants near APOE than what has been previously reported in non-Polynesian populations. The association with several known lipid loci combined with the newly identified associations with variants near MGAT1 and RAB21 suggest that while some of the genetic architecture of lipids is shared between Samoans and other populations, part of the genetic architecture may be Polynesian-specific.

ECHS1 disease in two unrelated families of Samoan descent: Common variant - rare disorder.

Mutations in the short-chain enoyl-CoA hydratase (SCEH) gene, ECHS1, cause a rare autosomal recessive disorder of valine catabolism. Patients usually present with developmental delay, regression, dystonia, feeding difficulties, and abnormal MRI with bilateral basal ganglia involvement. We present clinical, biochemical, molecular, and functional data for four affected patients from two unrelated families of Samoan descent with identical novel compound heterozygous mutations. Family 1 has three affected boys while Family 2 has an affected daughter, all with clinical and MRI findings of Leigh syndrome and intermittent episodes of acidosis and ketosis. WES identified a single heterozygous variant in ECHS1 at position c.832G > A (p.Ala278Thr). However, western blot revealed significantly reduced ECHS1 protein for all affected family members. Decreased SCEH activity in fibroblasts and a mild increase in marker metabolites in urine further supported ECHS1 as the underlying gene defect. Additional investigations at the DNA (aCGH, WGS) and RNA (qPCR, RT-PCR, RNA-Seq, RNA-Array) level identified a silent, common variant at position c.489G > A (p.Pro163=) as the second mutation. This substitution, present at high frequency in the Samoan population, is associated with decreased levels of normally spliced mRNA. To our understanding, this is the first report of a novel, hypomorphic allele c.489G > A (p.Pro163=), associated with SCEH deficiency.

AMD Genetics: Methods and Analyses for Association, Progression, and Prediction.

Age-related macular degeneration (AMD) is a multifactorial neurodegenerative disease, which is a leading cause of vision loss among the elderly in the developed countries. As one of the most successful examples of genome-wide association study (GWAS), a large number of genetic studies have been conducted to explore the genetic basis for AMD and its progression, of which over 30 loci were identified and confirmed. In this chapter, we review the recent development and findings of GWAS for AMD risk and progression. Then, we present emerging methods and models for predicting AMD development or its progression using large-scale genetic data. Finally, we discuss a set of novel statistical and analytical methods that were recently developed to tackle the challenges such as analyzing bilateral correlated eye-level outcomes that are subject to censoring with high-dimensional genetic data. Future directions for analytical studies of AMD genetics are also proposed.

Spinning convincing stories for both true and false association signals.

When interpreting genome-wide association peaks, it is common to annotate each peak by searching for genes with plausible relationships to the trait. However, "all that glitters is not gold"-one might interpret apparent patterns in the data as plausible even when the peak is a false positive. Accordingly, we sought to see how human annotators interpreted association results containing a mixture of peaks from both the original trait and a genetically uncorrelated "synthetic" trait. Two of us prepared a mix of original and synthetic peaks of three significance categories from five different scans along with relevant literature search results and then we all annotated these regions. Three annotators also scored the strength of evidence connecting each peak to the scanned trait and the likelihood of further studying that region. While annotators found original peaks to have stronger evidence (p Bonferroni = 0.017) and higher likelihood of further study ( p Bonferroni = 0.006) than synthetic peaks, annotators often made convincing connections between the synthetic peaks and the original trait, finding these connections 55% of the time. These results show that it is not difficult for annotators to make convincing connections between synthetic association signals and genes found in those regions.

Linear mixed models for association analysis of quantitative traits with next-generation sequencing data.

We develop linear mixed models (LMMs) and functional linear mixed models (FLMMs) for gene-based tests of association between a quantitative trait and genetic variants on pedigrees. The effects of a major gene are modeled as a fixed effect, the contributions of polygenes are modeled as a random effect, and the correlations of pedigree members are modeled via inbreeding/kinship coefficients. F -statistics and χ 2 likelihood ratio test (LRT) statistics based on the LMMs and FLMMs are constructed to test for association. We show empirically that the F -distributed statistics provide a good control of the type I error rate. The F -test statistics of the LMMs have similar or higher power than the FLMMs, kernel-based famSKAT (family-based sequence kernel association test), and burden test famBT (family-based burden test). The F -statistics of the FLMMs perform well when analyzing a combination of rare and common variants. For small samples, the LRT statistics of the FLMMs control the type I error rate well at the nominal levels α = 0.01 and 0.05 . For moderate/large samples, the LRT statistics of the FLMMs control the type I error rates well. The LRT statistics of the LMMs can lead to inflated type I error rates. The proposed models are useful in whole genome and whole exome association studies of complex traits.

Genome-wide analysis of disease progression in age-related macular degeneration.

Family- and population-based genetic studies have successfully identified multiple disease-susceptibility loci for Age-related macular degeneration (AMD), one of the first batch and most successful examples of genome-wide association study. However, most genetic studies to date have focused on case-control studies of late AMD (choroidal neovascularization or geographic atrophy). The genetic influences on disease progression are largely unexplored. We assembled unique resources to perform a genome-wide bivariate time-to-event analysis to test for association of time-to-late-AMD with ∼9 million variants on 2721 Caucasians from a large multi-center randomized clinical trial, the Age-Related Eye Disease Study. To our knowledge, this is the first genome-wide association study of disease progression (bivariate survival outcome) in AMD genetic studies, thus providing novel insights to AMD genetics. We used a robust Cox proportional hazards model to appropriately account for between-eye correlation when analyzing the progression time in the two eyes of each participant. We identified four previously reported susceptibility loci showing genome-wide significant association with AMD progression: ARMS2-HTRA1 (P = 8.1 × 10-43), CFH (P = 3.5 × 10-37), C2-CFB-SKIV2L (P = 8.1 × 10-10) and C3 (P = 1.2 × 10-9). Furthermore, we detected association of rs58978565 near TNR (P = 2.3 × 10-8), rs28368872 near ATF7IP2 (P = 2.9 × 10-8) and rs142450006 near MMP9 (P = 0.0006) with progression to choroidal neovascularization but not geographic atrophy. Secondary analysis limited to 34 reported risk variants revealed that LIPC and CTRB2-CTRB1 were also associated with AMD progression (P < 0.0015). Our genome-wide analysis thus expands the genetics in both development and progression of AMD and should assist in early identification of high risk individuals.

A missense variant in CREBRF is associated with taller stature in Samoans.

OBJECTIVES: Studies have demonstrated that rs373863828, a missense variant in CREBRF, is associated with a number of anthropometric traits including body mass index (BMI), obesity, percent body fat, hip circumference, and abdominal circumference. Given the biological relationship between height and adiposity, we hypothesized that the effect of this variant on BMI might be due in part to an association of this variant with height. METHODS: We tested the hypothesis that minor allele of rs373863828 is associated with height in a Samoan population in two adult cohorts and in a separate cohort of children (age 5-18 years old) using linear mixed modeling. RESULTS: We found evidence of a strong relationship between rs373863828 and greater mean height in Samoan adults (0.77 cm greater average height for each copy of the minor allele) with the same direction of effect in Samoan children. CONCLUSIONS: These results suggest that the missense variant rs373863828 in CREBRF, first identified through an association with larger BMI, may be related to an underlying biological mechanism affecting overall body size including stature.

Genetic Variability in the Iron Homeostasis Pathway and Patient Outcomes After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND/OBJECTIVE: Iron can be detrimental to most tissues both in excess and in deficiency. The brain in particular is highly susceptible to the consequences of excessive iron, especially during blood brain barrier disruption after injury. Preliminary evidence suggests that iron homeostasis is important during recovery after neurologic injury; therefore, the exploration of genetic variability in genes involved in iron homeostasis is an important area of patient outcomes research. The purpose of this study was to examine the relationship between tagging single nucleotide polymorphisms (SNPs) in candidate genes related to iron homeostasis and acute and long-term patient outcomes after aneurysmal subarachnoid hemorrhage (aSAH). METHODS: This study was a longitudinal, observational, candidate gene association study of participants with aSAH that used a two-tier design including tier 1 (discovery, n = 197) and tier 2 (replication, n = 277). Participants were followed during the acute outcome phase for development of cerebral vasospasm and delayed cerebral ischemia (DCI) and during the long-term outcome phase for death and gross functional outcome using the Glasgow Outcome Scale (GOS; poor = 1-3). Genetic association analyses were performed using a logistic regression model adjusted for age, sex, and Fisher grade. Approximate Bayes factors (ABF) and Bayesian false discovery probabilities (BFDP) were used to prioritize and interpret results. RESULTS: In tier 1, 235 tagging SNPs in 28 candidate genes were available for analysis and 26 associations (20 unique SNPs in 12 genes) were nominated for replication in tier 2. In tier 2, we observed an increase in evidence of association for three associations in the ceruloplasmin (CP) and cubilin (CUBN) genes. We observed an association of rs17838831 (CP) with GOS at 3 months (tier 2 results, odds ratio [OR] = 2.10, 95% confidence interval [CI] = 1.14-3.86, p = 0.018, ABF = 0.52, and BFDP = 70.8%) and GOS at 12 months (tier 2 results, OR = 1.86, 95% CI 0.98-3.52, p = 0.058, ABF = 0.72, and BFDP = 77.3%) as well as rs10904850 (CUBN) with DCI (tier 2 results, OR = 0.70, 95% CI 0.48-1.02, p = 0.064, ABF = 0.59, and BFDP = 71.8%). CONCLUSIONS: Among the genes examined, our findings support a role for CP and CUBN in patient outcomes after aSAH. In an effort to translate these findings into clinical utility and improve outcomes after aSAH, additional research is needed to examine the functional roles of these genes after aSAH.

Genetic Variability and Trajectories of DNA Methylation May Support a Role for HAMP in Patient Outcomes After Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND/OBJECTIVE: Preclinical evidence suggests that iron homeostasis is an important biological mechanism following aneurysmal subarachnoid hemorrhage (aSAH); however, this concept is underexplored in humans. This study examined the relationship between patient outcomes following aSAH and genetic variants and DNA methylation in the hepcidin gene (HAMP), a key regulator of iron homeostasis. METHODS: In this exploratory, longitudinal observational study, participants with verified aSAH were monitored for acute outcomes including cerebral vasospasm (CV) and delayed cerebral ischemia (DCI) and evaluated post-discharge at 3 and 12 months for long-term outcomes of death and functional status using the Modified Rankin Scale (mRS; poor = 3-6) and Glasgow Outcome Scale (GOS; poor = 1-3). Participants were genotyped for two genetic variants, and DNA methylation data were collected from serial cerebrospinal fluid over 14 days post-aSAH at eight methylation sites within HAMP. Participants were grouped based on their site-specific DNA methylation trajectory, with and without correcting for cell-type heterogeneity (CTH), and the associations between genetic variants and inferred DNA methylation trajectory groups and patient outcomes were tested. To correct for multiple testing, an empirical significance threshold was computed using permutation testing. RESULTS: Genotype data for rs10421768 and rs7251432 were available for 241 and 371 participants, respectively, and serial DNA methylation data were available for 260 participants. Acute outcome prevalence included CV in 45% and DCI in 37.1% of the overall sample. Long-term outcome prevalence at 3 and 12 months included poor GOS in 23% and 21%, poor mRS in 31.6% and 27.3%, and mortality in 15.1% and 18.2%, respectively, in the overall sample. Being homozygous for the rs7251432 variant allele was significantly associated with death at 3 months (p = 0.003) and was the only association identified that passed adjustment for multiple testing mentioned above. Suggestive associations (defined as trending toward significance, p value < 0.05, but not meeting empirical significance thresholds) were identified between the homozygous variant allele for rs7251432 and poor GOS and mRS at 3 months (both p = 0.04) and death at 12 months (p = 0.02). For methylation trajectory groups, no associations remained significant after correction for multiple testing. However, for methylation trajectory groups not adjusted for CTH, suggestive associations were identified between cg18149657 and poor GOS and mRS at 3 months (p = 0.003 and p = 0.04, respectively) and death at 3 months (p = 0.04), and between cg26283059 and DCI (p = 0.01). For methylation trajectory groups adjusted for CTH, suggestive associations were identified between cg02131995 and good mRS at 12 months (p = 0.02), and between cg26283059 and DCI (p = 0.01). CONCLUSIONS: This exploratory pilot study offers preliminary evidence that HAMP may play a role in patient outcomes after aSAH. Replication of this study and mechanistic investigation of the role of HAMP in patient outcomes after aSAH are needed.

Statistics for X-chromosome associations.

In a genome-wide association study (GWAS), association between genotype and phenotype at autosomal loci is generally tested by regression models. However, X-chromosome data are often excluded from published analyses of autosomes because of the difference between males and females in number of X chromosomes. Failure to analyze X-chromosome data at all is obviously less than ideal, and can lead to missed discoveries. Even when X-chromosome data are included, they are often analyzed with suboptimal statistics. Several mathematically sensible statistics for X-chromosome association have been proposed. The optimality of these statistics, however, is based on very specific simple genetic models. In addition, while previous simulation studies of these statistics have been informative, they have focused on single-marker tests and have not considered the types of error that occur even under the null hypothesis when the entire X chromosome is scanned. In this study, we comprehensively tested several X-chromosome association statistics using simulation studies that include the entire chromosome. We also considered a wide range of trait models for sex differences and phenotypic effects of X inactivation. We found that models that do not incorporate a sex effect can have large type I error in some cases. We also found that many of the best statistics perform well even when there are modest deviations, such as trait variance differences between the sexes or small sex differences in allele frequencies, from assumptions.

Discordant association of the CREBRF rs373863828 A allele with increased BMI and protection from type 2 diabetes in Maori and Pacific (Polynesian) people living in Aotearoa/New Zealand.

AIMS/HYPOTHESIS: The A (minor) allele of CREBRF rs373863828 has been associated with increased BMI and reduced risk of type 2 diabetes in the Samoan populations of Samoa and American Samoa. Our aim was to test rs373863828 for associations with BMI and the odds of type 2 diabetes, gout and chronic kidney disease (CKD) in Maori and Pacific (Polynesian) people living in Aotearoa/New Zealand. METHODS: Linear and logistic regression models were used to analyse the association of the A allele of CREBRF rs373863828 with BMI, log-transformed BMI, waist circumference, type 2 diabetes, gout and CKD in 2286 adults. The primary analyses were adjusted for age, sex, the first four genome-wide principal components and (where appropriate) BMI, waist circumference and type 2 diabetes. The primary analysis was conducted in ancestrally defined groups and association effects were combined using meta-analysis. RESULTS: For the A allele of rs373863828, the effect size was 0.038 (95% CI 0.022, 0.055, p = 4.8 × 10-6) for log-transformed BMI, with OR 0.59 (95% CI 0.47, 0.73, p = 1.9 × 10-6) for type 2 diabetes. There was no evidence for an association of genotype with variance in BMI (p = 0.13), and nor was there evidence for associations with serum urate (ß = 0.012 mmol/l, pcorrected = 0.10), gout (OR 1.00, p = 0.98) or CKD (OR 0.91, p = 0.59). CONCLUSIONS/INTERPRETATION: Our results in New Zealand Polynesian adults replicate, with very similar effect sizes, the association of the A allele of rs373863828 with higher BMI but lower odds of type 2 diabetes among Samoan adults living in Samoa and American Samoa.

Genetic risk models: Influence of model size on risk estimates and precision.

Disease risk estimation plays an important role in disease prevention. Many studies have found that the ability to predict risk improves as the number of risk single-nucleotide polymorphisms (SNPs) in the risk model increases. However, the width of the confidence interval of the risk estimate is often not considered in the evaluation of the risk model. Here, we explore how the risk and the confidence interval width change as more SNPs are added to the model in the order of decreasing effect size, using both simulated data and real data from studies of abdominal aortic aneurysms and age-related macular degeneration. Our results show that confidence interval width is positively correlated with model size and the majority of the bigger models have wider confidence interval widths than smaller models. Once the model size is bigger than a certain level, the risk does not shift markedly, as 100% of the risk estimates of the one-SNP-bigger models lie inside the confidence interval of the one-SNP-smaller models. We also created a confidence interval-augmented reclassification table. It shows that both more effective SNPs with larger odds ratios and less effective SNPs with smaller odds ratios contribute to the correct decision of whom to screen. The best screening strategy is selected and evaluated by the net benefit quantity and the reclassification rate. We suggest that individuals whose upper bound of their risk confidence interval is above the screening threshold, which corresponds to the population prevalence of the disease, should be screened.