Methodology and Recruitment of Probands and Their Families for the Genes in Myopia (GEM) Study

Do age-related macular degeneration genes show association with keratoconus?

Background

Keratoconus (KC) is a common corneal condition with an unknown gender predominance. Although numerous studies have investigated the genetic component of KC, no specific genes have yet been attributed to the condition. We recently reported posterior segment changes occurring in the eyes of KC patients. However, it is not clear whether these changes are part of KC pathogenesis or reflect changes in anatomical features of the eye manifested by changes at the cornea. Given retinal changes represent the main characteristics observed in age-related macular degeneration (AMD) and that pleiotropy has been demonstrated between different eye diseases, we wished to assess if known AMD associated genes were also associated with KC.

Methods

A total of 248 KC subjects and 366 non-KC (control) subjects were recruited from public and private clinics in Melbourne for this analysis. Nineteen single nucleotide polymorphisms (SNPs) previously associated with AMD, including rs10490924 (ARMS2/HTRA1), rs10737680 (CFH), rs13278062 (TNFRSF10A), rs1864163 (CETP), rs2230199 (C3), rs3130783 (IER3/DDR1), rs334353 (TGFBR1), rs3812111 (COL10A1), rs429608 (C2/CFB), rs4420638 (APOE), rs4698775 (CFI), rs5749482 (TIMP3), rs6795735 (ADAMTS9), rs8017304 (RAD51B), rs8135665 (SLC16A8), rs920915 (LIPC), rs943080 (VEGFA), rs9542236 (B3GALTL) and rs13081855 (COL8A1/FILIP1L), were genotyped in this cohort. Logistic regression was applied to evaluate the association between these SNPs and KC on both genders together, as well as each gender separately. Linear regression was also applied to assess the association between SNPs and corneal curvature. Bonferroni correction was applied to adjust for multiple testing.

Results

Genotyping data were available for 18 SNPs. The SNP, rs6795735 (ADAMTS9) was significantly associated with KC (p = 3.5 × 10^- 4) when both genders were assessed, whereas rs5749482 (TIMP3) was only associated in males (p = 7.7 × 10^- 4) following Bonferroni multiple correction. However, when the covariates of age and gender were included, the associations became non-significant. In addition, none of the SNPs appeared significant for corneal curvature.

Conclusions

Our study suggested a potential association of rs6795735 in the ADAMTS9 gene and rs5749482 in the TIMP3 gene in KC and that different associations may be gender specific. Overall, SNPs initially identified as associated with AMD following multiple correction may be further impacted by other factors such as age or gender and further studies are needed to resolve this issue.

Assessment of the association of matrix metalloproteinases with myopia, refractive error and ocular biometric measures in an Australian cohort

Extracellular matrix proteins have been implicated in protein remodelling of the sclera in refractive error. The matrix metalloproteinases (MMPs) falling into the collagenase (MMP1, MMP8, MMP13), gelatinase (MMP2, MMP9) and stromelysin (MMP3, MMP10, MMP11) functional groups are particularly important. We wished to assess their association with myopia, refractive error and ocular biometric measures in an Australian cohort. A total of 543 unrelated individuals of Caucasian ethnicity were genotyped including 269 myopes (≤−1.0D) and 274 controls (>−1.0D). Tag single nucleotide polymorphisms (SNPs) (n = 53) were chosen to encompass these eight MMPs. Association tests were performed using linear and logistic regression analysis with age and gender as covariates. Spherical equivalent, myopia, axial length, anterior chamber depth and corneal curvature were the phenotypes of interest. Initial findings indicated that the best p values for each trait were 0.02 for myopia at rs2274755 (MMP9), 0.02 for SE at both rs3740938 (MMP8) and rs131451 (MMP11), 0.01 for axial length at rs11225395 (MMP8), 0.01 for anterior chamber depth at rs498186 (MMP1) and 0.02 at rs10488 (MMP1). However, following correction for multiple testing, none of these SNPs remained statistically significant. Our data suggests that the MMPs in the collagenase, gelatinase and stromelysin categories do not appear to be associated with myopia, refractive error or ocular biometric measures in this cohort.

Characteristics of responders to a request for a buccal cell specimen among survivors of childhood cancer and their siblings

PURPOSE

Analysis of biological samples in large cohort studies may provide insight into the mechanism of, and risk factors for, disease onset and progression.

METHODS

This study describes the methods used to collect biological samples from a large multi-center cohort of childhood cancer survivors and siblings of childhood cancer survivors and evaluates the predictors of a positive response among these individuals.

RESULTS

Among survivors, female sex, white race/ethnicity, college graduation, never smoking, accessing the healthcare system in the past 2 years, and having a second malignant neoplasm were the strongest predictors of returning a sample. Among siblings, a similar demographic profile defined those likely to submit the requested sample.

CONCLUSION

To reduce selection bias and increase the value of these samples for future analysis, additional phone calls and reminders targeting non-responders are needed to improve response rates among those least likely to respond to a single mailed request.

The GEnes in Myopia (GEM) study in understanding the aetiology of refractive errors

Refractive errors represent the leading cause of correctable vision impairment and blindness in the world with an estimated 2 billion people affected. Refractive error refers to a group of refractive conditions including hypermetropia, myopia, astigmatism and presbyopia but relatively little is known about their aetiology. In order to explore the potential role of genetic determinants in refractive error the "GEnes in Myopia (GEM) study" was established in 2004. The findings that have resulted from this study have not only provided greater insight into the role of genes and other factors involved in myopia but have also gone some way to uncovering the aetiology of other refractive errors. This review will describe some of the major findings of the GEM study and their relative contribution to the literature, illuminate where the deficiencies are in our understanding of the development of refractive errors and how we will advance this field in the future.

Role of the hepatocyte growth factor gene in refractive error

OBJECTIVE

Refractive errors such as myopia and hypermetropia are among the leading causes of visual impairment worldwide. Several genetic loci have been associated with myopia but none to date have been reported for hypermetropia. We investigated the hepatocyte growth factor (HGF) as a candidate gene influencing these 2 refractive error states.

DESIGN

Case-control study.

PARTICIPANTS

A total of 551 individuals (193 males, 358 females; mean age, 55.41+/-12.65 years) including 117 individuals with high myopia <or= -6.00 diopters (D), 140 individuals with low/moderate myopia (-2.00 to -5.99 D), 148 emmetropic individuals (-0.50 to +0.75 D) and 146 hyperopic individuals (>+2.00 D) were included in the analysis from 3 different Australian population cohorts (The Genes in Myopia Study, the Blue Mountains Eye Study, and the Melbourne Visual impairment project).

METHODS

Genotyping of 9 tag single nucleotide polymorphisms (SNPs) that encompassed the entire HGF gene and its associated sequences as well as 6 additional SNPs identified through DNA resequencing was undertaken.

MAIN OUTCOME MEASURES

Genetic association with refraction.

RESULTS

After correction for multiple testing, the SNPs rs12536657 (odds ratio [OR], 5.53; 95% confidence interval [CI], 1.14-26.76) and rs5745718 (OR, 2.24; 95% CI, 1.30-3.85) showed significant association with hypermetropia. Whereas the SNPs rs1743 (OR, 2.02; 95% CI, 1.19-3.43; P = .009), rs4732402 (OR, 2.03; 95% CI, 1.23-3.36; P = 0.005), rs12536657 (OR, 2.38; 95% CI, 1.40-4.05; P = 0.001), rs10272030 (OR, 2.22; 95% CI, 1.31-3.75; P = 0.003), and rs9642131 (OR, 2.44; 95% CI, 1.43-4.14; P = 0.001) showed significant association with low/moderate myopia.

CONCLUSIONS

These findings present the HGF gene as the first gene significantly associated with hypermetropia as well as providing evidence of significant association with myopia in a second ethnic population. In addition, it provides insights into the important biological mechanisms that regulate human ocular development (emmetropization), which are currently poorly understood.

Pharmacogenetics of glatiramer acetate therapy for multiple sclerosis reveals drug-response markers

Genetic-based optimization of treatment prescription is becoming a central research focus in the management of chronic diseases, such as multiple sclerosis, which incur a prolonged drug-regimen adjustment. This study was aimed to identify genetic markers that can predict response to glatiramer acetate (Copaxone) immunotherapy for relapsing multiple sclerosis. For this purpose, we genotyped fractional cohorts of two glatiramer acetate clinical trials for HLA-DRB1*1501 and 61 single nucleotide polymorphisms within a total of 27 candidate genes. Statistical analyses included single nucleotide polymorphism-by-single nucleotide polymorphism and haplotype tests of drug-by-genotype effects in drug-treated versus placebo-treated groups. We report the detection of a statistically significant association between glatiramer acetate response and a single nucleotide polymorphism in a T-cell receptor beta (TRB@) variant replicated in the two independent cohorts (odds ratio=6.85). Findings in the Cathepsin S (CTSS) gene (P=0.049 corrected for all single nucleotide polymorphisms and definitions tested, odds ratio=11.59) in one of the cohorts indicate a possible association that needs to be further investigated. Additionally, we recorded nominally significant associations of response with five other genes, MBP, CD86, FAS, IL1R1 and IL12RB2, which are likely to be involved in glatiramer acetate's mode-of-action, both directly and indirectly. Each of these association signals in and of itself is consistent with the no-association null-hypothesis, but the number of detected associations is surprising vis-à-vis chance expectation. Moreover, the restriction of these associations to the glatiramer acetate-treated group, rather than the placebo group, clearly demonstrates drug-specific genetic effects. These findings provide additional progress toward development of pharmacogenetics-based personalized treatment for multiple sclerosis.

Evaluation of Accuracy in Proband-Reported Family History and Its Determinants: The Genes in Myopia Family Study

PURPOSE

Proband-reported family histories are widely used in epidemiological and genetic studies. The accuracy of these reports may have significant effects on the intended outcome, particularly in genetic studies. This study aims to determine the accuracy of proband-reported family history of myopia and to assess whether demographic or clinical factors are predictive of an accurate history.

METHODS

In 2004 to 2005, the study recruited 120 myopic probands (< or = -0.50 D spherical equivalent in both eyes) aged 18 to 72 years and 358 nuclear family members residing within Victoria, Australia as part of the Genes in Myopia (GEM) family study. Data collection used an examiner-administered questionnaire with an ocular examination. Proband-reported family history of myopia was evaluated for agreement with ophthalmic examination results of family members.

RESULTS

The statistical measures of accuracy used in this report were sensitivity, specificity, positive predictive value, and negative predictive value. Sensitivity varied from 85 to 98%, specificity from 84 to 96%, positive predictive value from 83 to 97%, and negative predictive value from 84 to 97%. Following multivariate analysis, an evaluation of demographic and clinical factors indicated that the highest predictive accuracy was obtained from proband reporting of their children [odds ratio (OR), 0.38; 95% confidence interval (CI), 0.15 to 0.94] whereas the most inaccurate reporting of a proband was when there was less-severe maternal myopia (per 0.50 D less myopic) (OR, 1.23; 95% CI, 1.06 to 1.43) or for increase in total education of the proband (per 1 year increase) (OR, 1.22; 95% CI, 1.04 to 1.42).

CONCLUSIONS

Several variables influence the accuracy of obtaining a family history of myopia. A questionnaire-based approach alone will introduce some error into the study and this should be taken into account when designing and undertaking family-based epidemiological or genetic studies of myopia.

Heritability and shared environment estimates for myopia and associated ocular biometric traits: the Genes in Myopia (GEM) family study

To examine the familial correlations, heritability (h(2)) and common environmental components (c(2)) of myopia and ocular biometric traits (all treated as continuous outcomes) in families collected through the Genes in Myopia (GEM) family study in Australia. A total of 132 pedigrees (723 participants) were recruited for this study. All individuals completed a risk factor questionnaire and underwent a detailed eye examination including spherical equivalent (SphE) and ocular biometric measurements of axial length (AL), anterior chamber depth (ACD) and corneal curvature (CC). Familial correlations were calculated and h(2) and c(2) were estimated using a variance component model that assumes a multivariate t distribution within each pedigree. Two definitions of common environments (c(2)) were considered: nuclear family (current) shared environment (Model 1) and sib-ship (childhood) shared environment (Model 2). Population ascertainment adjustment was performed using the Blue Mountains eye study dataset. The trends observed for familial correlations suggested that SphE is influenced by both environmental and genetic factors whereas AL, ACD and CC are predominantly genetically determined. This was largely confirmed by variance components modelling. Heritability estimates (adjusted for age, sex and years of education) from the best fitting ACE model (Model 2, childhood shared environment) were 0.50 +/- 0.05 for SphE, 0.73 +/- 0.04 for AL, 0.78 +/- 0.04 for ACD and 0.16 +/- 0.06 for CC. Childhood environmental effects were significant with c(2) estimated to be 0.33 +/- 0.04 for SphE, 0.06 +/- 0.03 for AL, 0.22 +/- 0.04 for ACD and 0.10 +/- 0.05 for CC. Age was associated with SphE, total years of education was associated with AL and sex was associated with all traits studied. We used a novel and conservative approach to account for and estimate common environmental effects by specifying either nuclear family or sib-ship environment when estimating heritability estimates and showed that all traits examined (SphE, AL, ACD and CC) are heritable, thus reflecting a genetic component. These traits therefore all represent candidates for quantitative trait linkage analyses.