Purpose

To evaluate the association between refractive error and the prevalence of glaucoma by race or ethnicity.

Design

Cross-sectional study.

Participants

Kaiser Permanente Northern California Health Plan members with refractive error measured at 35 years of age or older between 2008 and 2014 and with no history of cataract surgery, refractive surgery, or a corneal disorder.

Methods

We identified 34 040 members with glaucoma or ocular hypertension (OHTN; cases) and 403 398 members without glaucoma (controls). Glaucoma cases were classified as primary angle-closure glaucoma (PACG); 1 of the 4 forms of open-angle glaucoma: primary open-angle glaucoma (POAG), normal-tension glaucoma (NTG), pigmentary glaucoma (PIGM), and pseudoexfoliation glaucoma (PEX); or OHTN. Refractive error, expressed as spherical equivalent (SE), was coded as a continuous trait and also as categories. Logistic regression analyses were used to estimate the association between refractive error and the prevalence of glaucoma overall and in specific racial or ethnic groups.

Main outcome measures

The association between refractive error and glaucoma subtypes evaluated as odds ratios (ORs) with 95% confidence intervals (CIs).

Results

In controls, the mean SE was -0.59 diopters (D) (standard deviation, 2.62 D). Each 1-D reduction in SE was associated with a 22% decrease in the odds of PACG (OR, 0.78; 95% CI, 0.77-0.80) and with increases in the odds of open-angle glaucoma ranging from 1.23 (95% CI, 1.20-1.26) for PIGM, to 1.07 (95% CI, 1.03-1.11) for PEX, and to 1.05 (95% CI, 1.04-1.06) for OHTN. In addition, we observed a stronger association between myopia and POAG among non-Hispanic whites (OR, 1.12; 95% CI, 1.11-1.13) and NTG among Asians (OR, 1.17; 95% CI, 1.15-1.20) and non-Hispanic whites (OR, 1.19; 95% CI, 1.15-1.22).

Conclusions

Myopia was associated with an increased prevalence of all forms of open-angle glaucoma and OHTN, whereas hyperopia was associated with a substantially increased prevalence of PACG. Although high myopia is a strong risk factor for glaucoma subtypes, low and moderate myopia also have a significant effect on glaucoma risk. Additionally, there were moderate racial differences in the association of myopia with the risk of POAG and NTG.

Exome and whole-genome sequencing studies are becoming increasingly common, but little is known about the accuracy of the genotype calls made by the commonly used platforms. Here we use replicate high-coverage sequencing of blood and saliva DNA samples from four European-American individuals to estimate lower bounds on the error rates of Complete Genomics and Illumina HiSeq whole-genome and whole-exome sequencing. Error rates for nonreference genotype calls range from 0.1% to 0.6%, depending on the platform and the depth of coverage. Additionally, we found (1) no difference in the error profiles or rates between blood and saliva samples; (2) Complete Genomics sequences had substantially higher error rates than Illumina sequences had; (3) error rates were higher (up to 6%) for rare or unique variants; (4) error rates generally declined with genotype quality (GQ) score, but in a nonlinear fashion for the Illumina data, likely due to loss of specificity of GQ scores greater than 60; and (5) error rates increased with increasing depth of coverage for the Illumina data. These findings, especially (3)-(5), suggest that caution should be taken in interpreting the results of next-generation sequencing-based association studies, and even more so in clinical application of this technology in the absence of validation by other more robust sequencing or genotyping methods.

In pharmacogenomic studies of quantitative change, any association between genetic variants and the pretreatment (baseline) measurement can bias the estimate of effect between those variants and drug response. A putative solution is to adjust for baseline. We conducted a series of genome-wide association studies (GWASs) for low-density lipoprotein cholesterol (LDL-C) response to statin therapy in 34,874 participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort as a case study to investigate the impact of baseline adjustment on results generated from pharmacogenomic studies of quantitative change. Across phenotypes of statin-induced LDL-C change, baseline adjustment identified variants from six loci meeting genome-wide significance (SORT/CELSR2/PSRC1, LPA, SLCO1B1, APOE, APOB, and SMARCA4/LDLR). In contrast, baseline-unadjusted analyses yielded variants from three loci meeting the criteria for genome-wide significance (LPA, APOE, and SLCO1B1). A genome-wide heterogeneity test of baseline versus statin on-treatment LDL-C levels was performed as the definitive test for the true effect of genetic variants on statin-induced LDL-C change. These findings were generally consistent with the models not adjusting for baseline signifying that genome-wide significant hits generated only from baseline-adjusted analyses (SORT/CELSR2/PSRC1, APOB, SMARCA4/LDLR) were likely biased. We then comprehensively reviewed published GWASs of drug-induced quantitative change and discovered that more than half (59%) inappropriately adjusted for baseline. Altogether, we demonstrate that (1) baseline adjustment introduces bias in pharmacogenomic studies of quantitative change and (2) this erroneous methodology is highly prevalent. We conclude that it is critical to avoid this common statistical approach in future pharmacogenomic studies of quantitative change.

Background

Prior studies of the glycemic effect of statins have been inconsistent. Also, most studies have only considered a short duration of statin use; the effect of long-term statin use on fasting glucose (FG) has not been well examined. The aim of this work is to investigate the effect of long-term statin exposure on FG levels.

Methods

Using electronic health record (EHR) data from a large and diverse longitudinal cohort, we defined long-term statin exposure in two ways: the cumulative years of statin use (cumulative supply) and the years' supply-weighted sum of doses (cumulative dose). Simvastatin, lovastatin, atorvastatin and pravastatin were included in the analysis. The relationship between statin exposure and FG was examined using linear regression with mixed effects modeling, comparing statin users before and after initiating statins and statin never-users.

Results

We examined 593,130 FG measurements from 87,151 individuals over a median follow up of 20 years. Of these, 42,678 were never-users and 44,473 were statin users with a total of 730,031 statin prescriptions. FG was positively associated with cumulative supply of statin but not comulative dose when both measures were in the same model. While statistically significant, the annual increase in FG attributable to statin exposure was modest at only 0.14 mg/dl, with only slight and non-significant differences among statin types.

Conclusions

Elevation in FG level is associated with statin exposure, but the effect is modest. The results suggest that the risk of a clinically significant increase in FG attributable to long-term statin use is small for most individuals.

Body mass index (BMI), a proxy measure for obesity, is determined by both environmental (including ethnicity, age, and sex) and genetic factors, with > 400 BMI-associated loci identified to date. However, the impact, interplay, and underlying biological mechanisms among BMI, environment, genetics, and ancestry are not completely understood. To further examine these relationships, we utilized 427,509 calendar year-averaged BMI measurements from 100,418 adults from the single large multiethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We observed substantial independent ancestry and nationality differences, including ancestry principal component interactions and nonlinear effects. To increase the list of BMI-associated variants before assessing other differences, we conducted a genome-wide association study (GWAS) in GERA, with replication in the Genetic Investigation of Anthropomorphic Traits (GIANT) consortium combined with the UK Biobank (UKB), followed by GWAS in GERA combined with GIANT, with replication in the UKB. We discovered 30 novel independent BMI loci (P < 5.0 × 10^-8) that replicated. We then assessed the proportion of BMI variance explained by sex in the UKB using previously identified loci compared to previously and newly identified loci and found slight increases: from 3.0 to 3.3% for males and from 2.7 to 3.0% for females. Further, the variance explained by previously and newly identified variants decreased with increasing age in the GERA and UKB cohorts, echoed in the variance explained by the entire genome, which also showed gene-age interaction effects. Finally, we conducted a tissue expression QTL enrichment analysis, which revealed that GWAS BMI-associated variants were enriched in the cerebellum, consistent with prior work in humans and mice.

BACKGROUND: Adverse childhood experiences are demonstrated risk factors for depression, a common co-morbidity of multiple sclerosis, but are understudied among people with multiple sclerosis. OBJECTIVE: Estimate the association between adverse childhood experiences and depression among 1,990 adults with multiple sclerosis. METHODS: Participants were members of Kaiser Permanente Northern California from two studies between 2006 and 2021 and were diagnosed with multiple sclerosis by a neurologist. Adverse childhood experiences were assessed using two instruments, including the Behavioral Risk Factor Surveillance System. Participants self-reported ever experiencing a major depressive episode. Meta-analysis random effects models and logistic regression were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) to assess the relationship between adverse childhood experiences and a history of depression across study samples. Adverse childhood experiences were expressed as any/none, individual events, and counts. Models adjusted for sex, birth year, race, and ethnicity. RESULTS: Exposure to any adverse childhood experiences increased the odds of depression in people with multiple sclerosis (OR: 1.71, 95% CI: 1.21-2.42). Several individual adverse childhood experiences were also strongly associated with depression, including significant abuse or neglect (OR: 2.79, 95% CI: 2.11-3.68). CONCLUSION: Findings suggest that adverse childhood experiences are associated with depression among people with multiple sclerosis. Screening for depression should be done regularly, especially among people with multiple sclerosis with a history of adverse childhood experiences.

Although evidence exists for a causal association between 25-hydroxyvitamin D (25(OH)D) serum levels, and multiple sclerosis (MS), the role of variation in vitamin D receptor (VDR) binding in MS is unknown. Here, we leveraged previously identified variants associated with allele imbalance in VDR binding (VDR-binding variant; VDR-BV) in ChIP-exo data from calcitriol-stimulated lymphoblastoid cell lines and 25(OH)D serum levels from genome-wide association studies to construct genetic instrumental variables (GIVs). GIVs are composed of one or more genetic variants that serve as proxies for exposures of interest. Here, GIVs for both VDR-BVs and 25(OH)D were used in a two-sample Mendelian Randomization study to investigate the relationship between VDR binding at a locus, 25(OH)D serum levels, and MS risk. Data for 13,598 MS cases and 38,887 controls of European ancestry from Kaiser Permanente Northern California, Swedish MS studies, and the UK Biobank were included. We estimated the association between each VDR-BV GIV and MS. Significant interaction between a VDR-BV GIV and a GIV for serum 25OH(D) was evidence for a causal association between VDR-BVs and MS unbiased by pleiotropy. We observed evidence for associations between two VDR-BVs (rs2881514, rs2531804) and MS after correction for multiple tests. There was evidence of interaction between rs2881514 and a 25(OH)D GIV, providing evidence of a causal association between rs2881514 and MS. This study is the first to demonstrate evidence that variation in VDR binding at a locus contributes to MS risk. Our results are relevant to other autoimmune diseases in which vitamin D plays a role.

In pharmacogenomic studies of quantitative change, any association between genetic variants and the pretreatment (baseline) measurement can bias the estimate of effect between those variants and drug response. A putative solution is to adjust for baseline. We conducted a series of genome-wide association studies (GWASs) for low-density lipoprotein cholesterol (LDL-C) response to statin therapy in 34,874 participants of the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort as a case study to investigate the impact of baseline adjustment on results generated from pharmacogenomic studies of quantitative change. Across phenotypes of statin-induced LDL-C change, baseline adjustment identified variants from six loci meeting genome-wide significance (SORT/CELSR2/PSRC1, LPA, SLCO1B1, APOE, APOB, and SMARCA4/LDLR). In contrast, baseline-unadjusted analyses yielded variants from three loci meeting the criteria for genome-wide significance (LPA, APOE, and SLCO1B1). A genome-wide heterogeneity test of baseline versus statin on-treatment LDL-C levels was performed as the definitive test for the true effect of genetic variants on statin-induced LDL-C change. These findings were generally consistent with the models not adjusting for baseline signifying that genome-wide significant hits generated only from baseline-adjusted analyses (SORT/CELSR2/PSRC1, APOB, SMARCA4/LDLR) were likely biased. We then comprehensively reviewed published GWASs of drug-induced quantitative change and discovered that more than half (59%) inappropriately adjusted for baseline. Altogether, we demonstrate that (1) baseline adjustment introduces bias in pharmacogenomic studies of quantitative change and (2) this erroneous methodology is highly prevalent. We conclude that it is critical to avoid this common statistical approach in future pharmacogenomic studies of quantitative change.

Objectives

Determine the validity and reliability of a remote, technician-guided cognitive assessment for multiple sclerosis (MS), incorporating the Symbol Digit Modalities Test (SDMT) and the California Verbal Learning Test, Second Edition (CVLT-II).

Methods

In 100 patients, we compared conventional in-person testing to remote, web-assisted assessments, and in 36 patients, we assessed test-retest reliability using two equivalent, alternative forms.

Results

In-person and remote-administered SDMT (r = 0.85) and CVLT-II (r = 0.71) results were very similar. Reliability was adequate and alternative forms of SDMT (r = 0.92) and CVLT-II (r = 0.81) produced similar results.

Conclusions

Findings indicate remote assessment can provide valid, reliable measures of cognitive function in MS.