Reliability and validity of conjunctival ultraviolet autofluorescence measurement

BACKGROUND: Conjunctival ultraviolet autofluorescence (UVAF) photography was developed to detect and characterise pre-clinical sunlight-induced UV damage. The reliability of this measurement and its relationship to outdoor activity are currently unknown. METHODS: 599 people aged 16-85 years in the cross-sectional Norfolk Island Eye Study were included in the validation study. 196 UVAF individual photographs (49 people) and 60 UVAF photographs (15 people) of Norfolk Island Eye Study participants were used for intra- and inter-observer reliability assessment, respectively. Conjunctival UVAF was measured using UV photography. UVAF area was calculated using computerised methods by one grader on two occasions (intra-observer analysis) or two graders (inter-observer analysis). Outdoor activity category, during summer and winter separately, was determined with a UV questionnaire. Total UVAF equalled the area measured in four conjunctival areas (nasal/temporal conjunctiva of right and left eyes). RESULTS: Intra-observer (ρ_c=0.988, 95% CI 0.967 to 0.996, p<0.001), and inter-observer concordance correlation coefficients (ρ_c=0.924, 95% CI 0.870 to 0.956, p<0.001) of total UVAF exceeded 0.900. When grouped according to 10 mm(2) total UVAF increments, intra- and inter-observer reliability was very good (κ=0.81) and good (κ=0.71), respectively. Increasing time outdoors was strongly with increasing total UVAF in summer and winter (p(trend) <0.001). CONCLUSION: Intra- and inter-observer reliability of conjunctival UVAF is high. In this population, UVAF correlates strongly with the authors' survey-based assessment of time spent outdoors.

The association between time spent outdoors and myopia using a novel biomarker of outdoor light exposure

PURPOSE: We sought to determine whether conjunctival ultraviolet autofluorescence (UVAF), a biomarker of outdoor light exposure, is associated with myopia. METHODS: We performed a cross-sectional study on Norfolk Island and recruited individuals aged ≥ 15 years. Participants completed a sun-exposure questionnaire and underwent non-cycloplegic autorefraction. Conjunctival UVAF used a specially adapted electronic flash system fitted with UV-transmission filters (transmittance range 300-400 nm, peak 365 nm) as the excitation source. Temporal and nasal conjunctival UVAF was measured in both eyes using computerized photographic analysis with the sum referred to as "total UVAF." RESULTS: In 636 participants, prevalence of myopia decreased with an increasing quartile of total UVAF (P(trend) = 0.002). Median total UVAF was lower in subjects with myopia (spherical equivalent [SE] ≤ -1.0 diopter [D]) than participants without myopia: 16.6 mm(2) versus 28.6 mm(2), P = 0.001. In the multivariable model that adjusted for age, sex, smoking, cataract, height and weight, UVAF was independently associated with myopia (SE ≤ -1.0 D): odds ratio (OR) for total UVAF (per 10 mm(2)) was 0.81, 95% confidence interval (CI) 0.69 to 0.94, P = 0.007. UVAF was also significantly associated with myopia when analysis was restricted to subjects <50 years, and in moderate-severe myopia (SE ≤ -3.0 D). Prevalence of myopia decreased with increasing time outdoors (P(trend) = 0.03), but time outdoors was not associated with myopia on multivariable analysis. CONCLUSIONS: Study authors identified a protective association between increasing UVAF and myopia. The protective association of higher UVAF against myopia was stronger than that of increased levels of time spent outdoors as measured by this study's questionnaire. Future studies should investigate the association between UVAF and incident myopia, and its relationship to myopic progression.

The human μ-opioid receptor gene polymorphism (A118G) is associated with head pain severity in a clinical cohort of female migraine with aura patients

Migraine is a painful and debilitating, neurovascular disease. Current migraine head pain treatments work with differing efficacies in migraineurs. The opioid system plays an important role in diverse biological functions including analgesia, drug response and pain reduction. The A118G single nucleotide polymorphism (SNP) in exon 1 of the μ-opioid receptor gene (OPRM1) has been associated with elevated pain responses and decreased pain threshold in a variety of populations. The aim of the current preliminary study was to test whether genotypes of the OPRM1 A118G SNP are associated with head pain severity in a clinical cohort of female migraineurs. This was a preliminary study to determine whether genotypes of the OPRM1 A118G SNP are associated with head pain severity in a clinical cohort of female migraineurs. A total of 153 chronic migraine with aura sufferers were assessed for migraine head pain using the Migraine Disability Assessment Score instrument and classified into high and low pain severity groups. DNA was extracted and genotypes obtained for the A118G SNP. Logistic regression analysis adjusting for age effects showed the A118G SNP of the OPRM1 gene to be significantly associated with migraine pain severity in the test population (P = 0.0037). In particular, G118 allele carriers were more likely to be high pain sufferers compared to homozygous carriers of the A118 allele (OR = 3.125, 95 % CI = 1.41, 6.93, P = 0.0037). These findings suggest that A118G genotypes of the OPRM1 gene may influence migraine-associated head pain in females. Further investigations are required to fully understand the effect of this gene variant on migraine head pain including studies in males and in different migraine subtypes, as well as in response to head pain medication.

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.