Calculation of exact p-values when SNPs are tested using multiple genetic models

Variants of SLC2A10 may be Linked to Poor Response to Metformin

Purpose

A study among Filipinos revealed that only 15% of patients with diabetes achieved glycemic control, and poor response to metformin could be one of the possible reasons. Recent studies demonstrate how genetic variations influence response to metformin. Hence, the present study aimed to determine genetic variants associated with poor response to metformin.

Methods

Using a candidate variant approach, 195 adult Filipino participants with newly diagnosed type 2 diabetes mellitus (T2DM) were enrolled in a case-control study. Genomic DNA from blood samples were collected. Allelic and genotypic associations of variants with poor response to metformin were determined using exact statistical methods.

Results

Several polymorphisms were nominally associated with poor response to metformin (P_uncorr < 0.05). The most notable is the association of multiple variants in the SLC2A10 gene—rs2425911, rs3092412, and rs2425904—with common additive genetic mode of inheritance. Other variants that have possible associations with poor drug response include rs340874 (PROX-AS1), rs815815 (CALM2), rs1333049 (CDKN2B-AS1), rs2010963 (VEGFA), rs1535435 and rs9494266 (AHI1), rs11128347 (PDZRN3), rs1805081 (NPC1), and rs13266634 (SLC30A8).

Conclusion

In Filipinos, a trend for the association for several variants was noted, with further observation that several mechanisms may be involved. The results may serve as pilot data for further validation of candidate variants for T2DM pharmacotherapy.

Association of mannose-binding lectin 2 gene polymorphisms with Guillain-Barré syndrome

Complement activation plays a critical role in the pathogenesis of Guillain-Barré syndrome (GBS), a debilitating immune-mediated neuropathy. Mannose-binding lectin (MBL) is a complement activation factor of lectin pathway which as genetic host factor may influence the susceptibility or severity of GBS. We investigated the frequency of MBL2 promoter (- 550H/L and - 221X/Y) and functional region (exon 1 A/O) polymorphisms and their association with disease susceptibility, clinical features and serum MBL among GBS patients (n = 300) and healthy controls (n = 300) in Bangladesh. The median patient age was 30 years (IQR: 18-42; males, 68%). MBL2 polymorphisms were not significantly associated with GBS susceptibility compared to healthy controls. HL heterozygosity in GBS patients was significantly associated with mild functional disability at enrolment (P = 0.0145, OR, 95% CI 2.1, 1.17-3.82). The HY, YA, HA and HYA heterozygous haplotypes were more common among mildly affected (P = 0.0067, P = 0.0086, P = 0.0075, P = 0.0032, respectively) than severely affected patients with GBS. Reduced serum MBL was significantly associated with the LL, OO and no HYA variants and GBS disease severity. No significant association was observed between MBL2 polymorphisms and electrophysiological variants, recent Campylobacter jejuni infection or anti-ganglioside (GM1) antibody responses in GBS. In conclusion, MBL2 gene polymorphisms are related to reduced serum MBL and associated with the severity of GBS.

Suggestive evidence of genetic association of -572G > C polymorphism with primary open angle glaucoma in a North Indian Punjabi population

BACKGROUND

IL6 is an important candidate gene implicated in the pathogenesis of glaucoma. The present study assessed the genetic association of -174G > C and -572G > C polymorphisms in the IL6 promoter region with primary open angle glaucoma (POAG) and primary angle closure glaucoma (PACG) in a north Indian Punjabi cohort.

METHODS

910 subjects (313 POAG, 148 PACG cases and 449 controls) were recruited. Genotyping was done by TaqMan assays. Genetic association was tested under different genetic models using Plink. Diplotype and linkage disequilibrium (LD) analysis was done through Haploview. Association of clinical parameters with the genotypes was assessed by one-way ANOVA. Adjustment for potential confounding variables was done by binary logistic regression. IL6 levels were measured in POAG patients and controls.

RESULTS

572G > C variant showed marginal difference in genotype frequency between pooled cases and POAG subgroup with respect to controls (p = 0.042; OR = 1.33; and p = 0.041; OR = 1.37). The GC genotype conferred 1.37-fold protection under codominant model in POAG cases (p = 0.034, OR = 1.37, 95% CI = 1.02-1.85; p_corr = 0.025, OR = 1.45, 95% CI = 1.04-2.02). The mean value for IOP was elevated among cases having 'CC' genotype at the -572G > C locus (p = 0.037). Lower levels of IL6 were detected in POAG patients in plasma samples (p = 0.0001).

CONCLUSION

The study reports suggestive evidence for -572G > C variant in IL6 in affecting genetic susceptibility to POAG in the targeted North Indian Punjabi cohort. A correlation of IL6 levels in aqueous humor (AH) and systemic circulation in POAG was observed, the functional and diagnostic relevance of which may be further investigated.

Genetic association between CDKN2B/CDKN2B-AS1 gene polymorphisms with primary glaucoma in a North Indian cohort: an original study and an updated meta-analysis

Background

Variants in CDKN2B/CDKN2B-AS1 have been reported to modulate glaucoma risk in several GWAS across different populations. CDKN2B/CDKN2A encodes tumor suppressor proteins p16^INK4A/p15^INK4B which influences cell proliferation/senescence in RGCs, the degeneration of which is a risk factor for glaucoma. CDKN2B-AS1 codes a long non-coding RNA in antisense direction and is involved in influencing nearby CDKN2A/CDKN2B via regulatory mechanisms.

Methods

Current study investigated four SNPs (rs2157719, rs3217992, rs4977756, rs1063192) of aforementioned genes in a case–control study in a North Indian cohort. Genotyping was done with Taqman chemistry. In addition, an updated meta-analysis was performed.

Results

Two SNPs, rs3217992 and rs2157719 were found to be significantly associated with the disease. The frequency of ‘T’ allele of rs3217992 was significantly lower in cases (POAG/PACG) [p = 0.045; OR = 0.80(CI = 0.65–0.99) and p = 0.024; OR = 0.73(CI = 0.55–0.96)], respectively than in controls. Genetic model analysis revealed that TT + CT genotype confers 0.73-fold protection against POAG [p = 0.047; OR = 0.73(CI = 0.54–0.99)] and trend assumed additive model gives 0.53 times higher protection against PACG progression. However the association of rs3217992 with POAG and PACG did not remain significant after Bonferroni correction. For rs2157719, the ‘C’ allele was found to be less prevalent among cases (POAG/PACG) with respect to controls. Cochran Armitage trend test assuming additive model revealed 0.77 and 0.64-fold protection against POAG and PACG respectively. Bonferroni correction (p_corr= 0.003) was applied and the association of rs2157719 remained significant in PACG cases but not among POAG cases (p = 0.024). The ‘CC’ genotype also confers protection against primary glaucoma (POAG/PACG) among males and female subjects. The frequency rs1063192 and rs4977756 did not vary significantly among subjects, however the haplotype ‘CATA’ was found to be associated with increased glaucoma risk. An updated meta-analysis conducted on pooled studies on POAG cases and controls revealed significant association between rs1063192, rs2157719, rs4977756 and POAG except rs3217992.

Conclusion

The study concludes significant association between INK4 variants and primary glaucoma in the targeted North Indian Punjabi cohort. We believe that deep-sequencing of INK4 locus may help in identifying novel variants modifying susceptibility to glaucoma. Functional studies can further delineate the role of CDKN2B and CDKN2B-AS1 in primary glaucoma for therapeutic intervention.

Symptom cluster profiles following traumatic orthopedic injuries: A protocol

Traumatic injuries affect millions of Americans annually, resulting in $671 billion in healthcare costs and lost productivity. Postinjury symptoms, like pain, sleep disturbance, anxiety, depression, and stressor-related disorders are highly prevalent following traumatic orthopedic injuries (TOI) and may contribute to negative long-term outcomes. Symptoms rarely present in isolation, but in clusters of two or more symptoms that co-occur to affect health in aggregate. Identifying symptom cluster profiles following TOI may identify those at highest risk for negative outcomes. Dysregulation of brain-derived neurotrophic factor (BDNF) is a potential biological mechanism responsible for symptom cluster profile membership after TOI and may be targeted in future precision-health applications. The purpose of this paper is to present the protocol of a cross-sectional study designed to identify symptom cluster profiles and measure the extent to which the BDNF val66met mutation and serum concentration of BDNF are associated with membership in symptom cluster profiles. We plan to recruit 150 TOI survivors within the first 72 h of injury. The study aims are to (1) describe TOI survivors' membership in symptom cluster profiles, indicated by pain, sleep disturbance, and symptoms of anxiety, depression, and stressor-related disorders, immediately following a TOI; (2) examine associations between demographic and clinical factors and symptom cluster profile membership among TOI survivors; (3) test the hypothesis that low serum concentrations of BDNF are associated with membership among symptom cluster profiles following TOI; and (4) test the hypothesis that the presence of the val66met mutation on one or both alleles of the BDNF gene is associated with membership among symptom cluster profiles following TOI.

Power and Sample Size Calculations for Genetic Association Studies in the Presence of Genetic Model Misspecification

INTRODUCTION

When analyzing data from large-scale genetic association studies, such as targeted or genome-wide resequencing studies, it is common to assume a single genetic model, such as dominant or additive, for all tests of association between a given genetic variant and the phenotype. However, for many variants, the chosen model will result in poor model fit and may lack statistical power due to model misspecification.

OBJECTIVE

We develop power and sample size calculations for tests of gene and gene × environment interaction, allowing for misspecification of the true mode of genetic susceptibility.

METHODS

The power calculations are based on a likelihood ratio test framework and are implemented in an open-source R package ("genpwr").

RESULTS

We use these methods to develop an analysis plan for a resequencing study in idiopathic pulmonary fibrosis and show that using a 2-degree of freedom test can increase power to detect recessive genetic effects while maintaining power to detect dominant and additive effects.

CONCLUSIONS

Understanding the impact of model misspecification can aid in study design and developing analysis plans that maximize power to detect a range of true underlying genetic effects. In particular, these calculations help identify when a multiple degree of freedom test or other robust test of association may be advantageous.

Vitamin D insufficiency increases risk of chronic pain among African Americans experiencing motor vehicle collision

African Americans experience an increased burden of motor vehicle collision (MVC), post-MVC musculoskeletal pain, and vitamin D insufficiency. In this prospective multicenter study, we tested the hypothesis that African Americans (n = 133) presenting to the emergency department after MVC with low peritraumatic vitamin D levels would have worse chronic musculoskeletal pain outcomes compared to individuals with sufficient vitamin D. Vitamin D levels were assessed in the early aftermath of MVC through enzyme-linked immunosorbent assay, and pain severity was assessed using the 0 to 10 numeric rating scale at 6 weeks, 6 months, and 1 year. In repeated-measures analysis, African American MVC survivors with vitamin D insufficiency experienced more severe chronic pain (β = 1.18, P = 0.031). In secondary analyses, we assessed for evidence that the effect of vitamin D on post-MVC pain outcomes is mediated, at least in part, by the influence of vitamin D on genetic variants in genes involved in immune system regulation (IL-10 and NLRP3). Genotyping was performed using a genome-wide microarray using collected DNA samples. Secondary analyses suggest that the effect of vitamin D on post-MVC pain outcomes may be influenced by genetic variation in IL-10 and NLRP3. Further studies are needed to assess the impact of vitamin D insufficiency on pain outcomes in African Americans experiencing MVC and other common trauma exposures, to assess factors affecting this relationship, and to assess the efficacy of administering vitamin D in the immediate aftermath of MVC to prevent chronic pain. Such low-cost, nonopioid interventions are urgently needed to address chronic pain development after MVC.

Genetic Predisposition to Symptomatic Lumbar Disk Herniation in Pediatric and Young Adult Patients

STUDY DESIGN

Case-control whole-genome sequencing analysis of a highly select, young cohort with symptomatic lumbar disk herniation (LDH) compared with the standard variation in a large reference population.

OBJECTIVE

To assess genetic influences predisposing pediatric and young adult patients to symptomatic LDH.

SUMMARY OF BACKGROUND DATA

LDH has traditionally been attributed to natural weakening or mechanical insult, but recent literature supports a potential genetic influence.

METHODS

Young patients with symptomatic, clinically confirmed LDH who underwent surgical treatment were included. Patients were younger than the average age of presentation, limiting the influence of environmental risks. DNA collected from these patients was compared with a reference genome (1000 Genomes Project). A genome-wide association study using whole-genome sequencing was used to characterize genetic mutations potentially associated with LDH.

RESULTS

Among the 61 candidate genes flagged, 20 had missense mutations in 2 or more LDH cases. Missense mutations in collagen-encoding genes were observed in 12 of 15 patients (80%). A potential association with clinical presentation was indicated by odds ratios of key single-nucleotide polymorphism (SNP) variants in genes that encode collagen. Relative to the reference population, the LDH cohort demonstrated two statistically significant SNP variants in the gene encoding for aggrecan, a protein that facilitates load-bearing properties in the cartilaginous end plate. Aggrecan genes SNPs rs3817428 and rs11638262 were significantly associated with decreased odds of symptomatic LDH: odds ratio 0.05 (0.02-0.11) and 0.04 (0-0.26), respectively (P < 1 × 10 for both).

CONCLUSION

These results suggest that collagen-encoding variants may be a genetic risk factor for LDH. They also shed new light on the role of variants that impact aggrecan, which sustains the cartilaginous end plate. Genetic predisposition to LDH may therefore be related to a multimodal combination of mutations that affect the nucleus pulposus, annulus fibrosus, and the cartilaginous end plates.

LEVEL OF EVIDENCE

4.

Genetic model misspecification in genetic association studies

Objective

The underlying model of the genetic determinant of a trait is generally not known with certainty a priori. Hence, in genetic association studies, a dominant model might be erroneously modelled as additive, an error investigated previously. We explored this question, for candidate gene studies, by evaluating the sample size required to compensate for the misspecification and improve inference at the analysis stage. Power calculations were carried out with (1) the true dominant model and (2) the incorrect additive model. Empirical power, sample size and effect size were compared between scenarios (1) and (2). In each of the scenarios the estimates were evaluated for a rare (minor allele frequency < 0.01), low frequency (0.01 ≤ minor allele frequency < 0.05) and common (minor allele frequency ≥ 0.05) single nucleotide polymorphism.

Results

The results confirm the detrimental effect of the misspecification error on power and effect size for any minor allele frequency. The implications of the error are not negligible; therefore, candidate gene studies should consider the more conservative sample size to compensate for the effect of error. When it is not possible to extend the sample size, methods that help mitigate the impact of the error should be systematically used.

Electronic supplementary material

The online version of this article (10.1186/s13104-017-2911-3) contains supplementary material, which is available to authorized users.

Ridge, Lasso and Bayesian additive-dominance genomic models

Background

A complete approach for genome-wide selection (GWS) involves reliable statistical genetics models and methods. Reports on this topic are common for additive genetic models but not for additive-dominance models. The objective of this paper was (i) to compare the performance of 10 additive-dominance predictive models (including current models and proposed modifications), fitted using Bayesian, Lasso and Ridge regression approaches; and (ii) to decompose genomic heritability and accuracy in terms of three quantitative genetic information sources, namely, linkage disequilibrium (LD), co-segregation (CS) and pedigree relationships or family structure (PR). The simulation study considered two broad sense heritability levels (0.30 and 0.50, associated with narrow sense heritabilities of 0.20 and 0.35, respectively) and two genetic architectures for traits (the first consisting of small gene effects and the second consisting of a mixed inheritance model with five major genes).

Results

G-REML/G-BLUP and a modified Bayesian/Lasso (called BayesA*B* or t-BLASSO) method performed best in the prediction of genomic breeding as well as the total genotypic values of individuals in all four scenarios (two heritabilities x two genetic architectures). The BayesA*B*-type method showed a better ability to recover the dominance variance/additive variance ratio. Decomposition of genomic heritability and accuracy revealed the following descending importance order of information: LD, CS and PR not captured by markers, the last two being very close.

Conclusions

Amongst the 10 models/methods evaluated, the G-BLUP, BAYESA*B* (−2,8) and BAYESA*B* (4,6) methods presented the best results and were found to be adequate for accurately predicting genomic breeding and total genotypic values as well as for estimating additive and dominance in additive-dominance genomic models.