Heritable Risk and Protective Genetic Components of Glaucoma Medication Non-Adherence.

Glaucoma is the leading cause of irreversible blindness, affecting 76 million globally. It is characterized by irreversible damage to the optic nerve. Pharmacotherapy manages intraocular pressure (IOP) and slows disease progression. However, non-adherence to glaucoma medications remains problematic, with 41-71% of patients being non-adherent to their prescribed medication. Despite substantial investment in research, clinical effort, and patient education protocols, non-adherence remains high. Therefore, we aimed to determine if there is a substantive genetic component behind patients' glaucoma medication non-adherence. We assessed glaucoma medication non-adherence with prescription refill data from the Marshfield Clinic Healthcare System's pharmacy dispensing database. Two standard measures were calculated: the medication possession ratio (MPR) and the proportion of days covered (PDC). Non-adherence on each metric was defined as less than 80% medication coverage over 12 months. Genotyping was done using the Illumina HumanCoreExome BeadChip in addition to exome sequencing on the 230 patients (1) to calculate the heritability of glaucoma medication non-adherence and (2) to identify SNPs and/or coding variants in genes associated with medication non-adherence. Ingenuity pathway analysis (IPA) was utilized to derive biological meaning from any significant genes in aggregate. Over 12 months, 59% of patients were found to be non-adherent as measured by the MPR80, and 67% were non-adherent as measured by the PDC80. Genome-wide complex trait analysis (GCTA) suggested that 57% (MPR80) and 48% (PDC80) of glaucoma medication non-adherence could be attributed to a genetic component. Missense mutations in TTC28, KIAA1731, ADAMTS5, OR2W3, OR10A6, SAXO2, KCTD18, CHCHD6, and UPK1A were all found to be significantly associated with glaucoma medication non-adherence by whole exome sequencing after Bonferroni correction (p < 10-3) (PDC80). While missense mutations in TINAG, CHCHD6, GSTZ1, and SEMA4G were found to be significantly associated with medication non-adherence by whole exome sequencing after Bonferroni correction (p < 10-3) (MPR80). The same coding SNP in CHCHD6 which functions in Alzheimer's disease pathophysiology was significant by both measures and increased risk for glaucoma medication non-adherence by three-fold (95% CI, 1.62-5.8). Although our study was underpowered for genome-wide significance, SNP rs6474264 within ZMAT4 (p = 5.54 × 10-6) was found to be nominally significant, with a decreased risk for glaucoma medication non-adherence (OR, 0.22; 95% CI, 0.11-0.42)). IPA demonstrated significant overlap, utilizing, both standard measures including opioid signaling, drug metabolism, and synaptogenesis signaling. CREB signaling in neurons (which is associated with enhancing the baseline firing rate for the formation of long-term potentiation in nerve fibers) was shown to have protective associations. Our results suggest a substantial heritable genetic component to glaucoma medication non-adherence (47-58%). This finding is in line with genetic studies of other conditions with a psychiatric component (e.g., post-traumatic stress disorder (PTSD) or alcohol dependence). Our findings suggest both risk and protective statistically significant genes/pathways underlying glaucoma medication non-adherence for the first time. Further studies investigating more diverse populations with larger sample sizes are needed to validate these findings.

Mild Neurological Signs in FMR1 Premutation Women in an Unselected Community-Based Cohort.

BACKGROUND: Premutation-sized (55-200) CGG repeat expansions in the FMR1 gene cause fragile X-associated tremor/ataxia syndrome (FXTAS). Most studies of premutation carriers utilized reverse ascertainment to identify patients, leading to a selection bias for larger repeats. As shorter CGG premutation repeats are common in the population, understanding their impact on health outcomes has a potentially large public health footprint. OBJECTIVE: The study's objective was to compare an unselected group of premutation carriers (n = 35, 55-101 CGG repeats) with matched controls (n = 61, 29-39 CGG repeats) with respect to FXTAS-type signs using structured neurological assessments. METHODS: Three neurologists independently rated signs, using an adapted version of the FXTAS Rating Scale (Leehey MA, Berry-Kravis E, Goetz CG, et al. FMR1 CGG repeat length predicts motor dysfunction in premutation carriers. Neurology. 2008). This was a double-blind study, as genetic status (premutation vs. control) was known neither by the participants nor by any of the neurologists. Analyses controlled potentially confounding comorbid conditions in the electronic health record (eg, osteoarthritis and stroke) and probed the association of age with signs. RESULTS: Although there was no overall difference between carriers and controls, among individuals without any potentially confounding comorbid diagnoses, there was a statistically significant age-associated elevation in FXTAS-type signs in premutation carriers compared to controls. CONCLUSIONS: Among those who do not have other comorbid diagnoses, women who have CGG repeats at the lower end of the premutation range may be at greater risk for ataxia and parkinsonism than their age peers, although their overall risk of developing such clinical features is low. This study should provide reassurance to those who share characteristics with the present cohort. © 2021 International Parkinson and Movement Disorder Society.

Public Attitudes toward Consent and Data Sharing in Biobank Research: A Large Multi-site Experimental Survey in the US.

Individuals participating in biobanks and other large research projects are increasingly asked to provide broad consent for open-ended research use and widespread sharing of their biosamples and data. We assessed willingness to participate in a biobank using different consent and data sharing models, hypothesizing that willingness would be higher under more restrictive scenarios. Perceived benefits, concerns, and information needs were also assessed. In this experimental survey, individuals from 11 US healthcare systems in the Electronic Medical Records and Genomics (eMERGE) Network were randomly allocated to one of three hypothetical scenarios: tiered consent and controlled data sharing; broad consent and controlled data sharing; or broad consent and open data sharing. Of 82,328 eligible individuals, exactly 13,000 (15.8%) completed the survey. Overall, 66% (95% CI: 63%-69%) of population-weighted respondents stated they would be willing to participate in a biobank; willingness and attitudes did not differ between respondents in the three scenarios. Willingness to participate was associated with self-identified white race, higher educational attainment, lower religiosity, perceiving more research benefits, fewer concerns, and fewer information needs. Most (86%, CI: 84%-87%) participants would want to know what would happen if a researcher misused their health information; fewer (51%, CI: 47%-55%) would worry about their privacy. The concern that the use of broad consent and open data sharing could adversely affect participant recruitment is not supported by these findings. Addressing potential participants' concerns and information needs and building trust and relationships with communities may increase acceptance of broad consent and wide data sharing in biobank research.

Probing the Virtual Proteome to Identify Novel Disease Biomarkers.

BACKGROUND: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a "virtual proteomic" approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals. METHODS: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651). RESULTS: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate q<0.1. Among these, 13 associations involved lipid (n=7) or atherosclerosis (n=6) phenotypes. We tested each association for validation in MDCS using directly measured protein levels. At Bonferroni-adjusted significance thresholds, levels of apolipoprotein E isoforms were associated with hyperlipidemia, and circulating C-type lectin domain family 1 member B and platelet-derived growth factor receptor-ß predicted subclinical atherosclerosis. Odds ratios for carotid atherosclerosis were 1.31 (95% CI, 1.08-1.58; P=0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66-0.94; P=0.008) per 1-SD increment in platelet-derived growth factor receptor-ß. CONCLUSIONS: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.

Applying family analyses to electronic health records to facilitate genetic research.

Motivation: Pedigree analysis is a longstanding and powerful approach to gain insight into the underlying genetic factors in human health, but identifying, recruiting and genotyping families can be difficult, time consuming and costly. Development of high throughput methods to identify families and foster downstream analyses are necessary. Results: This paper describes simple methods that allowed us to identify 173 368 family pedigrees with high probability using basic demographic data available in most electronic health records (EHRs). We further developed and validate a novel statistical method that uses EHR data to identify families more likely to have a major genetic component to their diseases risk. Lastly, we showed that incorporating EHR-linked family data into genetic association testing may provide added power for genetic mapping without additional recruitment or genotyping. The totality of these results suggests that EHR-linked families can enable classical genetic analyses in a high-throughput manner. Availability and implementation: Pseudocode is provided as supplementary information. Contact: HEBBRING.SCOTT@marshfieldresearch.org. Supplementary information: Supplementary data are available at Bioinformatics online.

Epistatic Gene-Based Interaction Analyses for Glaucoma in eMERGE and NEIGHBOR Consortium.

Primary open angle glaucoma (POAG) is a complex disease and is one of the major leading causes of blindness worldwide. Genome-wide association studies have successfully identified several common variants associated with glaucoma; however, most of these variants only explain a small proportion of the genetic risk. Apart from the standard approach to identify main effects of variants across the genome, it is believed that gene-gene interactions can help elucidate part of the missing heritability by allowing for the test of interactions between genetic variants to mimic the complex nature of biology. To explain the etiology of glaucoma, we first performed a genome-wide association study (GWAS) on glaucoma case-control samples obtained from electronic medical records (EMR) to establish the utility of EMR data in detecting non-spurious and relevant associations; this analysis was aimed at confirming already known associations with glaucoma and validating the EMR derived glaucoma phenotype. Our findings from GWAS suggest consistent evidence of several known associations in POAG. We then performed an interaction analysis for variants found to be marginally associated with glaucoma (SNPs with main effect p-value <0.01) and observed interesting findings in the electronic MEdical Records and GEnomics Network (eMERGE) network dataset. Genes from the top epistatic interactions from eMERGE data (Likelihood Ratio Test i.e. LRT p-value <1e-05) were then tested for replication in the NEIGHBOR consortium dataset. To replicate our findings, we performed a gene-based SNP-SNP interaction analysis in NEIGHBOR and observed significant gene-gene interactions (p-value <0.001) among the top 17 gene-gene models identified in the discovery phase. Variants from gene-gene interaction analysis that we found to be associated with POAG explain 3.5% of additional genetic variance in eMERGE dataset above what is explained by the SNPs in genes that are replicated from previous GWAS studies (which was only 2.1% variance explained in eMERGE dataset); in the NEIGHBOR dataset, adding replicated SNPs from gene-gene interaction analysis explain 3.4% of total variance whereas GWAS SNPs alone explain only 2.8% of variance. Exploring gene-gene interactions may provide additional insights into many complex traits when explored in properly designed and powered association studies.

Penetrance of Hemochromatosis in HFE Genotypes Resulting in p.Cys282Tyr and p.[Cys282Tyr];[His63Asp] in the eMERGE Network.

Hereditary hemochromatosis (HH) is a common autosomal-recessive disorder associated with pathogenic HFE variants, most commonly those resulting in p.Cys282Tyr and p.His63Asp. Recommendations on returning incidental findings of HFE variants in individuals undergoing genome-scale sequencing should be informed by penetrance estimates of HH in unselected samples. We used the eMERGE Network, a multicenter cohort with genotype data linked to electronic medical records, to estimate the diagnostic rate and clinical penetrance of HH in 98 individuals homozygous for the variant coding for HFE p.Cys282Tyr and 397 compound heterozygotes with variants resulting in p.[His63Asp];[Cys282Tyr]. The diagnostic rate of HH in males was 24.4% for p.Cys282Tyr homozygotes and 3.5% for compound heterozygotes (p < 0.001); in females, it was 14.0% for p.Cys282Tyr homozygotes and 2.3% for compound heterozygotes (p < 0.001). Only males showed differences across genotypes in transferrin saturation levels (100% of homozygotes versus 37.5% of compound heterozygotes with transferrin saturation > 50%; p = 0.003), serum ferritin levels (77.8% versus 33.3% with serum ferritin > 300 ng/ml; p = 0.006), and diabetes (44.7% versus 28.0%; p = 0.03). No differences were found in the prevalence of heart disease, arthritis, or liver disease, except for the rate of liver biopsy (10.9% versus 1.8% [p = 0.013] in males; 9.1% versus 2% [p = 0.035] in females). Given the higher rate of HH diagnosis than in prior studies, the high penetrance of iron overload, and the frequency of at-risk genotypes, in addition to other suggested actionable adult-onset genetic conditions, opportunistic screening should be considered for p.[Cys282Tyr];[Cys282Tyr] individuals with existing genomic data.

Pilot screening study of targeted genetic polymorphisms for association with seasonal influenza hospital admission.

Host response to influenza is highly variable, suggesting a potential role of host genetic variation. To investigate the host genetics of severe influenza in a targeted fashion, 32 single nucleotide polymorphisms (SNPs) within viral immune response genes were evaluated for association with seasonal influenza hospitalization in an adult study population with European ancestry. SNP allele and genotype frequencies were compared between hospitalized influenza patients (cases) and population controls in a case-control study that included a discovery group (26 cases and 993 controls) and two independent, validation groups (1 with 84 cases and 4076 controls; the other with 128 cases and 9187 controls). Cases and controls had similar allele frequencies for variant rs12252 in interferon-inducible transmembrane protein 3 (IFITM3) (P > 0.05), and the study did not replicate the previously reported association of rs12252 with hospitalized influenza. In the discovery group, the preliminary finding of an association with a nonsense polymorphism (rs8072510) within the schlafen family member 13 (SFLN13) gene (P = 0.0099) was not confirmed in either validation group. Neither rs12252 nor rs8072510 showed an association according to the presence of clinical risk factors for influenza complications (P > 0.05), suggesting that these factors did not modify associations between the SNPs and hospitalized influenza. No other SNPs showed a statistically significant association with hospitalized influenza. Further research is needed to identify genetic factors involved in host response to seasonal influenza infection and to assess whether rs12252, a low-frequency variant in Europeans, contributes to influenza severity in populations with European ancestry.

Phenome-wide association study maps new diseases to the human major histocompatibility complex region.

BACKGROUND: Over 160 disease phenotypes have been mapped to the major histocompatibility complex (MHC) region on chromosome 6 by genome-wide association study (GWAS), suggesting that the MHC region as a whole may be involved in the aetiology of many phenotypes, including unstudied diseases. The phenome-wide association study (PheWAS), a powerful and complementary approach to GWAS, has demonstrated its ability to discover and rediscover genetic associations. The objective of this study is to comprehensively investigate the MHC region by PheWAS to identify new phenotypes mapped to this genetically important region. METHODS: In the current study, we systematically explored the MHC region using PheWAS to associate 2692 MHC-linked variants (minor allele frequency ≥0.01) with 6221 phenotypes in a cohort of 7481 subjects from the Marshfield Clinic Personalized Medicine Research Project. RESULTS: Findings showed that expected associations previously identified by GWAS could be identified by PheWAS (eg, psoriasis, ankylosing spondylitis, type I diabetes and coeliac disease) with some having strong cross-phenotype associations potentially driven by pleiotropic effects. Importantly, novel associations with eight diseases not previously assessed by GWAS (eg, lichen planus) were also identified and replicated in an independent population. Many of these associated diseases appear to be immune-related disorders. Further assessment of these diseases in 16 484 Marshfield Clinic twins suggests that some of these diseases, including lichen planus, may have genetic aetiologies. CONCLUSIONS: These results demonstrate that the PheWAS approach is a powerful and novel method to discover SNP-disease associations, and is ideal when characterising cross-phenotype associations, and further emphasise the importance of the MHC region in human health and disease.

Is Low FMR1 CGG Repeat Length in Males Correlated with Family History of BRCA-Associated Cancers? An Exploratory Analysis of Medical Records.

The FMR1 gene has been studied extensively with regard to expansions and premutations, but much less research has focused on potential effects of low CGG repeat length. Previous studies have demonstrated that BRCA1/2 positive women are more likely to have an FMR1 genotype with one low CGG allele, and that women with both FMR1 alleles in the low CGG repeat range are more likely to have had breast cancer compared to women with normal numbers of CGG repeats. However, there has been no research as to whether low CGG repeat length impacts cancer risks in men. Therefore, this study aimed to examine cancer incidence and related risk factors in men with low CGG repeat length in the FMR1 gene. We utilized subject data from the Marshfield Personalized Medicine Research Project to compare cancer-related diagnoses between 878 males with low CGG repeat length (< 24 repeats) and 368 male controls with CGG repeats in the normal range (24 to 40 repeats). We utilized ICD-9 codes to examine various cancer diagnoses, family histories of cancer, other non-malignant neoplasms, cancer surveillance, and genetic susceptibility. Men with low CGG repeats were identified to have significantly higher rates of family history of any cancer type (p = 0.011), family history of any BRCA-associated cancer (p = 0.002), and specifically, family history of prostate cancer (p = 0.007). The mean number of BRCA-associated cancer diagnoses (breast, prostate, pancreatic, and melanoma) per individual in the low CGG group was slightly higher than that of the control group, with this difference trending toward significance (p = 0.091). Additionally, men with low CGG repeats had significantly higher rates of connective/soft tissue neoplasms (p = 0.026). Additional research is needed to replicate the observations reported in this preliminary exploratory study, particularly including verification of ICD-9 codes and family history by a genetic counselor.

Regulatory polymorphisms in human DBH affect peripheral gene expression and sympathetic activity.

RATIONALE: Dopamine ß-hydroxylase (DBH) catalyzes the conversion of dopamine to norepinephrine in the central nervous system and peripherally. DBH variants are associated with large changes in circulating DBH and implicated in multiple disorders; yet causal relationships and tissue-specific effects remain unresolved. OBJECTIVE: To characterize regulatory variants in DBH, effect on mRNA expression, and role in modulating sympathetic tone and disease risk. METHODS AND RESULTS: Analysis of DBH mRNA in human tissues confirmed high expression in the locus coeruleus and adrenal gland, but also in sympathetically innervated organs (liver>lung>heart). Allele-specific mRNA assays revealed pronounced allelic expression differences in the liver (2- to 11-fold) attributable to promoter rs1611115 and exon 2 rs1108580, but only small differences in locus coeruleus and adrenals. These alleles were also associated with significantly reduced mRNA expression in liver and lung. Although DBH protein is expressed in other sympathetically innervated organs, mRNA levels were too low for analysis. In mice, hepatic Dbh mRNA levels correlated with cardiovascular risk phenotypes. The minor alleles of rs1611115 and rs1108580 were associated with sympathetic phenotypes, including angina pectoris. Testing combined effects of these variants suggested protection against myocardial infarction in 3 separate clinical cohorts. CONCLUSIONS: We demonstrate profound effects of DBH variants on expression in 2 sympathetically innervated organs, liver and lung, but not in adrenals and brain. Preliminary results demonstrate an association of these variants with clinical phenotypes responsive to peripheral sympathetic tone. We hypothesize that in addition to endocrine effects via circulating DBH and norepinephrine, the variants act in sympathetically innervated target organs.

SeqHBase: a big data toolset for family based sequencing data analysis.

BACKGROUND: Whole-genome sequencing (WGS) and whole-exome sequencing (WES) technologies are increasingly used to identify disease-contributing mutations in human genomic studies. It can be a significant challenge to process such data, especially when a large family or cohort is sequenced. Our objective was to develop a big data toolset to efficiently manipulate genome-wide variants, functional annotations and coverage, together with conducting family based sequencing data analysis. METHODS: Hadoop is a framework for reliable, scalable, distributed processing of large data sets using MapReduce programming models. Based on Hadoop and HBase, we developed SeqHBase, a big data-based toolset for analysing family based sequencing data to detect de novo, inherited homozygous, or compound heterozygous mutations that may contribute to disease manifestations. SeqHBase takes as input BAM files (for coverage at every site), variant call format (VCF) files (for variant calls) and functional annotations (for variant prioritisation). RESULTS: We applied SeqHBase to a 5-member nuclear family and a 10-member 3-generation family with WGS data, as well as a 4-member nuclear family with WES data. Analysis times were almost linearly scalable with number of data nodes. With 20 data nodes, SeqHBase took about 5 secs to analyse WES familial data and approximately 1 min to analyse WGS familial data. CONCLUSIONS: These results demonstrate SeqHBase's high efficiency and scalability, which is necessary as WGS and WES are rapidly becoming standard methods to study the genetics of familial disorders.

Association of Arrhythmia-Related Genetic Variants With Phenotypes Documented in Electronic Medical Records.

IMPORTANCE: Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants. OBJECTIVE: To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes. DESIGN, SETTING, AND PARTICIPANTS: This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014. EXPOSURES: One or more variants designated as pathogenic in SCN5A or KCNH2. MAIN OUTCOMES AND MEASURES: Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review. RESULTS: Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, -5% to +13%; P = .35). In the 1270 (63%) with ECGs, corrected QT intervals were not different in variant carriers vs those without (median, 429 vs 439 milliseconds; difference, -10 milliseconds; 95% CI, -16 to +3 milliseconds; P = .17). After manual review, 22 of 63 participants (35%) with designated variants had any ECG or arrhythmia phenotype, and only 2 had corrected QT interval longer than 500 milliseconds. CONCLUSIONS AND RELEVANCE: Among laboratories experienced in genetic testing for cardiac arrhythmia disorders, there was low concordance in designating SCN5A and KCNH2 variants as pathogenic. In an unselected population, the putatively pathogenic genetic variants were not associated with an abnormal phenotype. These findings raise questions about the implications of notifying patients of incidental genetic findings.

Prevalence estimation for monogenic autosomal recessive diseases using population-based genetic data.

Genetic methods can complement epidemiological surveys and clinical registries in determining prevalence of monogenic autosomal recessive diseases. Several large population-based genetic databases, such as the NHLBI GO Exome Sequencing Project, are now publically available. By assuming Hardy-Weinberg equilibrium, the frequency of individuals homozygous in the general population for a particular pathogenic allele can be directly calculated from a sample of chromosomes where some harbor the pathogenic allele. Further assuming that the penetrance of the pathogenic allele(s) is known, the prevalence of recessive phenotypes can be determined. Such work can inform public health efforts for rare recessive diseases. A Bayesian estimation procedure has yet to be applied to the problem of estimating disease prevalence from large population-based genetic data. A Bayesian framework is developed to derive the posterior probability density of monogenic, autosomal recessive phenotypes. Explicit equations are presented for the credible intervals of these disease prevalence estimates. A primary impediment to performing accurate disease prevalence calculations is the determination of truly pathogenic alleles. This issue is discussed, but in many instances remains a significant barrier to investigations solely reliant on statistical interrogation--functional studies can provide important information for solidifying evidence of variant pathogenicity. We also discuss several challenges to these efforts, including the population structure in the sample of chromosomes, the treatment of allelic heterogeneity, and reduced penetrance of pathogenic variants. To illustrate the application of these methods, we utilized recently published genetic data collected on a large sample from the Schmiedeleut Hutterites. We estimate prevalence and calculate 95% credible intervals for 13 autosomal recessive diseases using these data. In addition, the Bayesian estimation procedure is applied to data from a central European study of hereditary fructose intolerance. The methods described herein show a viable path to robustly estimating both the expected prevalence of autosomal recessive phenotypes and corresponding credible intervals using population-based genetic databases that have recently become available. As these genetic databases increase in number and size with the advent of cost-effective next-generation sequencing, we anticipate that these methods and approaches may be helpful in recessive disease prevalence calculations, potentially impacting public health management, health economic analyses, and treatment of rare diseases.

Differential Lipid Response to Statins Is Associated With Variants in the BUD13-APOA5 Gene Region.

Genetic variants within the BUD13-APOA5 gene region are known to be associated with high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) levels. Recent studies suggest that single nucleotide polymorphisms (SNPs) within this region affect HDL-C response to statin-fibrate combination therapy and low-density lipoprotein cholesterol (LDL-C) response to statin therapy. We hypothesized that SNPs within the BUD13-APOA5 region are associated with TG, HDL-C, and LDL-C response to statin therapy. We examined 1520 observations for 1086 patients from the Personalized Medicine Research Project, a large biorepository at the Marshfield Clinic Research Foundation, who had received statin therapy and been previously genotyped for polymorphisms in the 11q23 chromosomal region. A significant differential response to statin therapy was observed for 3 SNPs. The minor allele at rs11605293 significantly attenuated TG-lowering response to pravastatin (P = 0.000159), whereas the minor allele at rs12806755 was associated with a similar response to lovastatin (P = 0.000192). Genotypes at rs947990 significantly attenuated LDL-C reduction to atorvastatin therapy (P = 0.000668) with some patients with the minor allele having LDL-C increase after therapy. No SNPs within the BUD13-APOA5 region were associated with a significant effect on HDL-C reduction in response to statin therapy. In conclusion, this study suggests that common SNPs within the BUD13-APOA5 can affect TG and LDL-C response to statin therapy in a North American population.

Does levodopa improve vision in albinism? Results of a randomized, controlled clinical trial.

BACKGROUND: Dopamine is an intermediate product in the biosynthesis of melanin pigment, which is absent or reduced in albinism. Animal research has shown that supplying a precursor to dopamine, levodopa, may improve visual acuity in albinism by enhancing neural networks. This study examines the safety and effectiveness of levodopa on best-corrected visual acuity in human subjects with albinism. DESIGN: Prospective, randomized, placebo-controlled, double-masked clinical trial conducted at the University of Minnesota. PARTICIPANTS: Forty-five subjects with albinism. METHODS: Subjects with albinism were randomly assigned to one of three treatment arms: levodopa 0.76 mg/kg with 25% carbidopa, levodopa 0.51 mg/kg with 25% carbidopa, or placebo and followed for 20 weeks, with best-corrected visual acuity measured at enrollment, and at weeks 5, 10, 15, and 20 after enrollment. Side-effects were recorded with a symptom survey. Blood was drawn for genotyping. MAIN OUTCOME MEASURES: Side-effects and best-corrected visual acuity 20 weeks after enrolment. RESULTS: All subjects had at least one mutation found in a gene known to cause albinism. Mean age was 14.5 years (range: 3.5 to 57.8 years). Follow up was 100% and compliance was good. Minor side-effects were reported; there were no serious adverse events. There was no statistically significant improvement in best-corrected visual acuity after 20 weeks with either dose of levodopa. CONCLUSIONS: Levodopa, in the doses used in this trial and for the time course of administration, did not improve visual acuity in subjects with albinism.

Quantitative Foveal Structural Metrics as Predictors of Visual Acuity in Human Albinism.

Purpose: To assess the degree to which quantitative foveal structural measurements account for variation in best-corrected visual acuity (BCVA) in human albinism. Methods: BCVA was measured and spectral domain optical coherence tomography (SD-OCT) images were acquired for 74 individuals with albinism. Categorical foveal hypoplasia grades were assessed using the Leicester Grading System for Foveal Hypoplasia. Foveal anatomical specialization (foveal versus parafoveal value) was quantified for inner retinal layer (IRL) thickness, outer segment (OS) length, and outer nuclear layer (ONL) thickness. These metrics, participant sex, and age were used to build a multiple linear regression of BCVA. This combined linear model's predictive properties were compared to those of categorical foveal hypoplasia grading. Results: The cohort included three participants with type 1a foveal hypoplasia, 23 participants with type 1b, 33 with type 2, ten with type 3, and five with type 4. BCVA ranged from 0.08 to 1.00 logMAR (mean ± SD: 0.53 ± 0.21). IRL ratio, OS ratio, and ONL ratio were measured in all participants and decreased with increasing severity of foveal hypoplasia. The best-fit combined linear model included all three quantitative metrics and participant age expressed as a binary variable (divided into 0-18 years and 19 years or older; adjusted R2 = 0.500). This model predicted BCVA more accurately than a categorical foveal hypoplasia model (adjusted R2 = 0.352). Conclusions: A quantitative model of foveal specialization accounts for more variance in BCVA in albinism than categorical foveal hypoplasia grading. Other factors, such as optical aberrations and eye movements, may account for the remaining unexplained variance.

Mutations in Grxcr1 are the basis for inner ear dysfunction in the pirouette mouse.

Recessive mutations at the mouse pirouette (pi) locus result in hearing loss and vestibular dysfunction due to neuroepithelial defects in the inner ear. Using a positional cloning strategy, we have identified mutations in the gene Grxcr1 (glutaredoxin cysteine-rich 1) in five independent allelic strains of pirouette mice. We also provide sequence data of GRXCR1 from humans with profound hearing loss suggesting that pirouette is a model for studying the mechanism of nonsyndromic deafness DFNB25. Grxcr1 encodes a 290 amino acid protein that contains a region of similarity to glutaredoxin proteins and a cysteine-rich region at its C terminus. Grxcr1 is expressed in sensory epithelia of the inner ear, and its encoded protein is localized along the length of stereocilia, the actin-filament-rich mechanosensory structures at the apical surface of auditory and vestibular hair cells. The precise architecture of hair cell stereocilia is essential for normal hearing. Loss of function of Grxcr1 in homozygous pirouette mice results in abnormally thin and slightly shortened stereocilia. When overexpressed in transfected cells, GRXCR1 localizes along the length of actin-filament-rich structures at the dorsal-apical surface and induces structures with greater actin filament content and/or increased lengths in a subset of cells. Our results suggest that deafness in pirouette mutants is associated with loss of GRXCR1 function in modulating actin cytoskeletal architecture in the developing stereocilia of sensory hair cells.

Implementing genomic medicine in the clinic: the future is here.

Although the potential for genomics to contribute to clinical care has long been anticipated, the pace of defining the risks and benefits of incorporating genomic findings into medical practice has been relatively slow. Several institutions have recently begun genomic medicine programs, encountering many of the same obstacles and developing the same solutions, often independently. Recognizing that successful early experiences can inform subsequent efforts, the National Human Genome Research Institute brought together a number of these groups to describe their ongoing projects and challenges, identify common infrastructure and research needs, and outline an implementation framework for investigating and introducing similar programs elsewhere. Chief among the challenges were limited evidence and consensus on which genomic variants were medically relevant; lack of reimbursement for genomically driven interventions; and burden to patients and clinicians of assaying, reporting, intervening, and following up genomic findings. Key infrastructure needs included an openly accessible knowledge base capturing sequence variants and their phenotypic associations and a framework for defining and cataloging clinically actionable variants. Multiple institutions are actively engaged in using genomic information in clinical care. Much of this work is being done in isolation and would benefit from more structured collaboration and sharing of best practices.Genet Med 2013:15(4):258-267.

FMR1 CGG expansions: prevalence and sex ratios.

We have estimated the prevalence of FMR1 premutation and gray zone CGG repeat expansions in a population-based sample of 19,996 male and female adults in Wisconsin and compared the observed sex ratios of the prevalence of FMR1 CGG premutation and gray zone expansions to theoretical sex ratios. The female premutation prevalence was 1 in 148 and comparable to past research, but the male premutation prevalence of 1 in 290 is somewhat higher than most previous estimates. The female:male premutation prevalence ratio is in line with the theoretically predicted sex ratio. The prevalence of CGG repeats in the gray zone (45-54 repeats) was 1 in 33 females and 1 in 62 males. The prevalence of the "expanded" gray zone (defined here as 41-54 CGG repeats) was 1 in 14 females and 1 in 22 males, leading to a female:male ratio of 1.62 (95% confidence interval 1.39-1.90). This female:male ratio was significantly lower than the expected ratio of 2.0. We examined results from three previously published FMR1 prevalence studies and found similar female:male ratios for CGG repeats in this "expanded" gray zone range (pooled female:male ratio across all four studies 1.66, 95% confidence interval 1.51-1.82). Further research is needed to understand the apparent excess prevalence of males with CGG repeats in this range.