A multi-cohort genome-wide association study in African ancestry individuals reveals risk loci for primary open-angle glaucoma.

Primary open-angle glaucoma (POAG), the leading cause of irreversible blindness worldwide, disproportionately affects individuals of African ancestry. We conducted a genome-wide association study (GWAS) for POAG in 11,275 individuals of African ancestry (6,003 cases; 5,272 controls). We detected 46 risk loci associated with POAG at genome-wide significance. Replication and post-GWAS analyses, including functionally informed fine-mapping, multiple trait co-localization, and in silico validation, implicated two previously undescribed variants (rs1666698 mapping to DBF4P2; rs34957764 mapping to ROCK1P1) and one previously associated variant (rs11824032 mapping to ARHGEF12) as likely causal. For individuals of African ancestry, a polygenic risk score (PRS) for POAG from our mega-analysis (African ancestry individuals) outperformed a PRS from summary statistics of a much larger GWAS derived from European ancestry individuals. This study quantifies the genetic architecture similarities and differences between African and non-African ancestry populations for this blinding disease.

Mechanosensitive ion channel gene survey suggests potential roles in primary open angle glaucoma.

Although glaucoma is a disease modulated by eye pressure, the mechanisms of pressure sensing in the eye are not well understood. Here, we investigated associations between mechanosensitive ion channel gene variants and primary open-angle glaucoma (POAG). Common (minor allele frequency > 5%) single nucleotide polymorphisms located within the genomic regions of 20 mechanosensitive ion channel genes in the K2P, TMEM63, PIEZO and TRP channel families were assessed using genotype data from the NEIGHBORHOOD consortium of 3853 cases and 33,480 controls. Rare (minor allele frequency < 1%) coding variants were assessed using exome array genotyping data for 2606 cases and 2606 controls. Association with POAG was analyzed using logistic regression adjusting for age and sex. Two rare PIEZO1 coding variants with protective effects were identified in the NEIGHBOR dataset: R1527H, (OR 0.17, P = 0.0018) and a variant that alters a canonical splice donor site, g.16-88737727-C-G Hg38 (OR 0.38, P = 0.02). Both variants showed similar effects in the UK Biobank and the R1527H also in the FinnGen database. Several common variants also reached study-specific thresholds for association in the NEIGHBORHOOD dataset. These results identify novel variants in several mechanosensitive channel genes that show associations with POAG, suggesting that these channels may be potential therapeutic targets.

Mitochondrial TXNRD2 and ME3 Genetic Risk Scores Are Associated with Specific Primary Open-Angle Glaucoma Phenotypes.

PURPOSE: Genetic variants in regions that include the mitochondrial genes thioredoxin reductase 2 (TXNRD2) and malic enzyme 3 (ME3) are associated with primary open-angle glaucoma (POAG) in genome-wide association studies (GWASs). To assess their clinical impact, we investigated whether TXNRD2 and ME3 genetic risk scores (GRSs) are associated with specific glaucoma phenotypes. DESIGN: Cross-sectional study. PARTICIPANTS: A total of 2617 patients with POAG and 2634 control participants from the National Eye Institute Glaucoma Human Genetics Collaboration Hereditable Overall Operational Database (NEIGHBORHOOD) consortium. METHODS: All POAG-associated single nucleotide polymorphisms (SNPs) in the TXNRD2 and ME3 loci were identified using GWAS data (P < 0.05). Of these, 20 TXNRD2 and 24 ME3 SNPs were selected after adjusting for linkage disequilibrium. The correlation between SNP effect size and gene expression levels was investigated using the Gene-Tissue Expression database. Genetic risk scores were constructed for each individual using the unweighted sum of TXNRD2, ME3, and TXNRD2 + ME3 combined risk alleles. Age- and sex-adjusted odds ratios (ORs) for POAG diagnosis were calculated per decile for each GRS. Additionally, the clinical features of patients with POAG in the top 1%, 5%, and 10% of each GRS were compared with those in the bottom 1%, 5%, and 10%, respectively. MAIN OUTCOME MEASURES: Primary open-angle glaucoma OR per GRS decile, maximum treated intraocular pressure (IOP), and prevalence of paracentral visual field loss among patients with POAG with high versus low GRSs. RESULTS: A larger SNP effect size strongly correlated with higher TXNRD2 and lower ME3 expression levels (r = 0.95 and r = -0.97, respectively; P < 0.05 for both). Individuals in decile 10 of the TXNRD2 + ME3 GRS had the highest odds of POAG diagnosis (OR, 1.79 compared with decile 1; 95% confidence interval, 1.39-2.30; P < 0.001). Patients with POAG in the top 1% of the TXNRD2 GRS showed higher mean maximum treated IOP compared with the bottom 1% (19.9 mmHg vs. 15.6 mmHg; adjusted P = 0.03). Patients with POAG in the top 1% of the ME3 and TXNRD2 + ME3 GRS showed a higher prevalence of paracentral field loss than the bottom 1% (72.7% vs. 14.3% for ME3 GRS and 88.9% vs. 33.3% for TXNRD2+ME3 GRS; adjusted P = 0.03 for both). CONCLUSIONS: Patients with POAG with higher TXNRD2 and ME3 GRSs showed higher treated IOP and a greater prevalence of paracentral field loss. Functional studies exploring how these variants impact mitochondrial function in patients with glaucoma are warranted. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Diversity is key for cross-ancestry transferability of glaucoma genetic risk scores in Hispanic Veterans in the Million Veteran Program.

A major goal of precision medicine is to stratify patients based on their genetic risk for a disease to inform future screening and intervention strategies. For conditions like primary open-angle glaucoma (POAG), the genetic risk architecture is complicated with multiple variants contributing small effects on risk. Following the tepid success of genome-wide association studies for high-effect disease risk variant discovery, genetic risk scores (GRS), which collate effects from multiple genetic variants into a single measure, have shown promise for disease risk stratification. We assessed the application of GRS for POAG risk stratification in Hispanic-descent (HIS) and European-descent (EUR) Veterans in the Million Veteran Program. Unweighted and cross-ancestry meta-weighted GRS were calculated based on 127 genomic variants identified in the most recent report of cross-ancestry POAG meta-analyses. We found that both GRS types were associated with POAG case-control status and performed similarly in HIS and EUR Veterans. This trend was also seen in our subset analysis of HIS Veterans with less than 50% EUR global genetic ancestry. Our findings highlight the importance of evaluating GRS based on known POAG risk variants in different ancestry groups and emphasize the need for more multi-ancestry POAG genetic studies.

Evaluation of Restrictions on Tobacco Sales to Youth Younger Than 21 Years in Cleveland, Ohio, Area.

Importance: Tobacco 21 (T21) policies raise the minimum legal age to purchase tobacco from 18 to 21 years to curb youth access to tobacco products. While some studies have found that T21 is associated with reducing prevalence of youth tobacco use, little is known about the impact it may have on youth of different racial and ethnic identities. Objective: To evaluate the association of T21 policy with the prevalence of high school youth tobacco use across sex, race, and ethnicity. Design, Setting, and Participants: This survey study used representative survey data collected from the local biennial Youth Risk Behavior Survey from 2013 to 2017 comparing Cleveland, Ohio (which has a T21 policy), to proximal jurisdictions in the first-ring suburbs in Cuyahoga County (which do not have T21 policies). Within-Cleveland demographic information was also collected for 2013 to 2019. Overall high school youth tobacco use rates were compared between Cleveland and the first-ring suburbs and then examined within Cleveland among Hispanic, non-Hispanic Black, and non-Hispanic White high school students. Percentage data were adjusted to more closely align with local population demographics. Data were analyzed from January to June 2022. Exposures: T21 was implemented in Cleveland in 2016 and not adopted in proximal jurisdictions or at the state and federal level until at least 1 year later. Main Outcomes and Measures: The main outcomes were prevalence of past 30-day cigarette, cigar product, or e-cigarette use, measured using geographically representative high school youth survey data from 2013 to 2015 (prelegislation) and 2017 to 2019 (postlegislation) and compared using a difference-in-differences analysis. Results: The unweighted sample included 12 616 high school students (27.0% [95% CI, 26.9%-28.0%] in 10th grade; 50.9% [95% CI, 50.3%-51.6%] females) participating in 1 or more Youth Risk Behavior Surveys from 2013 to 2019, including 7064 students in Cleveland and 5552 students in the first-ring suburbs. Compared with the first-ring suburbs, Cleveland had a greater proportion of younger students (1623 [28.5%] ninth grade students vs 2179 [34.0%] ninth grade students) and Hispanic students (436 students [1.1%] vs 1433 students [12.6%]) and non-Hispanic Black students (2000 students [53.1%] vs 3971 students [75.1%]). Cigars were the most commonly used tobacco product in Cleveland, with use reported by 6201 students (19.8%) in 2013, 5877 students (21.3%) in 2015, and 5784 students (16.8%) in 2019. Compared with the first-ring suburbs, there was a greater decline in prevalence of use of cigars in Cleveland (ß = 0.18 [SE, 0.05]; P < .001). The disparity across race, ethnicity, and sex decreased for all current tobacco product use. For example, the maximum difference between demographic subpopulations in current cigarette use was 11.6 (95% CI, 9.5-13.7) percentage points in 2013 between White females (16.1% [95% CI, 11.3%-20.8%]) and Black males (4.5% [95% CI, 3.5%-5.4%]). This maximum difference in current cigarette use decreased significantly to 5.1 (95% CI, 3.5-6.7) percentage points in 2019 between White females (6.9% [95% CI, 3.4%-10.3%]) and Black females (1.8% [95% CI, 0.7%-2.8%]). Conclusions and Relevance: This survey study found that there was a decline in youth-reported tobacco use across every tobacco product category from 2013 to 2019. This decline changed the trajectory of use among several demographic groups and brought the youth populations with the highest tobacco product use to similar rates of others.

Glaucoma Genetic Risk Scores in the Million Veteran Program.

PURPOSE: Primary open-angle glaucoma (POAG) is a degenerative eye disease for which early treatment is critical to mitigate visual impairment and irreversible blindness. POAG-associated loci individually confer incremental risk. Genetic risk score(s) (GRS) could enable POAG risk stratification. Despite significantly higher POAG burden among individuals of African ancestry (AFR), GRS are limited in this population. A recent large-scale, multi-ancestry meta-analysis identified 127 POAG-associated loci and calculated cross-ancestry and ancestry-specific effect estimates, including in European ancestry (EUR) and AFR individuals. We assessed the utility of the 127-variant GRS for POAG risk stratification in EUR and AFR Veterans in the Million Veteran Program (MVP). We also explored the association between GRS and documented invasive glaucoma surgery (IGS). DESIGN: Cross-sectional study. PARTICIPANTS: MVP Veterans with imputed genetic data, including 5830 POAG cases (445 with IGS documented in the electronic health record) and 64 476 controls. METHODS: We tested unweighted and weighted GRS of 127 published risk variants in EUR (3382 cases and 58 811 controls) and AFR (2448 cases and 5665 controls) Veterans in the MVP. Weighted GRS were calculated using effect estimates from the most recently published report of cross-ancestry and ancestry-specific meta-analyses. We also evaluated GRS in POAG cases with documented IGS. MAIN OUTCOME MEASURES: Performance of 127-variant GRS in EUR and AFR Veterans for POAG risk stratification and association with documented IGS. RESULTS: GRS were significantly associated with POAG (P < 5 × 10-5) in both groups; a higher proportion of EUR compared with AFR were consistently categorized in the top GRS decile (21.9%-23.6% and 12.9%-14.5%, respectively). Only GRS weighted by ancestry-specific effect estimates were associated with IGS documentation in AFR cases; all GRS types were associated with IGS in EUR cases. CONCLUSIONS: Varied performance of the GRS for POAG risk stratification and documented IGS association in EUR and AFR Veterans highlights (1) the complex risk architecture of POAG, (2) the importance of diverse representation in genomics studies that inform GRS construction and evaluation, and (3) the necessity of expanding diverse POAG-related genomic data so that GRS can equitably aid in screening individuals at high risk of POAG and who may require more aggressive treatment.

Development and Evaluation of a Rules-based Algorithm for Primary Open-Angle Glaucoma in the VA Million Veteran Program.

The availability of electronic health record (EHR)-linked biobank data for research presents opportunities to better understand complex ocular diseases. Developing accurate computable phenotypes for ocular diseases for which gold standard diagnosis includes imaging remains inaccessible in most biobank-linked EHRs. The objective of this study was to develop and validate a computable phenotype to identify primary open-angle glaucoma (POAG) through accessing the Department of Veterans Affairs (VA) Computerized Patient Record System (CPRS) and Million Veteran Program (MVP) biobank. Accessing CPRS clinical ophthalmology data from VA Medical Center Eye Clinic (VAMCEC) patients, we developed and iteratively refined POAG case and control algorithms based on clinical, prescription, and structured diagnosis data (ICD-CM codes). Refinement was performed via detailed chart review, initially at a single VAMCEC (n = 200) and validated at two additional VAMCECs (n = 100 each). Positive and negative predictive values (PPV, NPV) were computed as the proportion of CPRS patients correctly classified with POAG or without POAG, respectively, by the algorithms, validated by ophthalmologists and optometrists with access to gold-standard clinical diagnosis data. The final algorithms performed better than previously reported approaches in assuring the accuracy and reproducibility of POAG classification (PPV >83% and NPV >97%) with consistent performance in Black or African American and in White Veterans. Applied to the MVP to identify cases and controls, genetic analysis of a known POAG-associated locus further validated the algorithms. We conclude that ours is a viable approach to use combined EHR-genetic data to study patients with complex diseases that require imaging confirmation.

Diversity in Polygenic Risk of Primary Open-Angle Glaucoma.

Glaucoma is the leading cause of irreversible blindness worldwide. Primary open-angle glaucoma (POAG), the most common glaucoma subtype, is more prevalent and severe in individuals of African ancestry. Unfortunately, this ancestral group has been historically under-represented among genetic studies of POAG. Moreover, both genetic and polygenic risk scores (GRS, PRS) that are typically based on genetic data from European-descent populations are not transferable to individuals without a majority of European ancestry. Given the aspirations of leveraging genetic information for precision medicine, GRS and PRS demonstrate clinical potential but fall short, in part due to the lack of diversity in these studies. Prioritizing diversity in the discovery of risk variants will improve the performance and utility of GRS and PRS-derived risk estimation for disease stratification, which could bring about earlier POAG intervention and treatment for a disease that often goes undetected until significant damage has occurred.

The role of genetic polymorphisms in executive functioning performance in temporal lobe epilepsy.

OBJECTIVE: To explore the role of several genetic polymorphisms (APOE ε4, BDNF Met, and COMT Val) in executive functioning performance in patients with pharmacoresistant temporal lobe epilepsy (TLE). METHODS: Ninety-three adults (51 female, mean age = 39 years) with TLE completed executive functioning measures as part of a comprehensive preoperative neuropsychological evaluation, including Trail Making Test (Part B), Wisconsin Card Sorting Test (Conceptual Level Responses and Perseverative Errors), Color Word Interference from the Delis Kaplan Executive Function System, and measures of phonemic and semantic verbal fluency. Genotyping of the APOE, BDNF, and COMT genes was conducted using DNA extracted from peripheral blood or brain tissue (from epilepsy surgery). RESULTS: After adjustment for general cognitive ability, COMT Val carriers showed poorer performance on semantic verbal fluency and color word interference than non-carriers, and BDNF Met carriers showed poorer performance on phonemic verbal fluency than those without a Met allele. SIGNIFICANCE: Results suggest that COMT and BDNF polymorphisms are associated with performance on several EF measures in patients with TLE, including tasks assessing verbal fluency and response inhibition and account for up to 16% of the variance in test performance. The APOE polymorphism was not significantly associated with any of the executive function measures analyzed.

Polygenic Risk Scores.

As genome-wide association studies have continued to identify loci associated with complex traits, the implications of and necessity for proper use of these findings, including prediction of disease risk, have become apparent. Many complex diseases have numerous associated loci with detectable effects implicating risk for or protection from disease. A common contemporary approach to using this information for disease prediction is through the application of genetic risk scores. These scores estimate an individual's liability for a specific outcome by aggregating the effects of associated loci into a single measure as described in the previous version of this article. Although genetic risk scores have traditionally included variants that meet criteria for genome-wide significance, an extension known as the polygenic risk score has been developed to include the effects of more variants across the entire genome. Here, we describe common methods and software packages for calculating and interpreting polygenic risk scores. In this revised version of the article, we detail information that is needed to perform a polygenic risk score analysis, considerations for planning the analysis and interpreting results, as well as discussion of the limitations based on the choices made. We also provide simulated sample data and a walkthrough for four different polygenic risk score software. © 2021 Wiley Periodicals LLC.

The GGLEAM Study: Understanding Glaucoma in the Ohio Amish.

Glaucoma leads to millions of cases of visual impairment and blindness around the world. Its susceptibility is shaped by both environmental and genetic risk factors. Although over 120 risk loci have been identified for glaucoma, a large portion of its heritability is still unexplained. Here we describe the foundation of the Genetics of GLaucoma Evaluation in the AMish (GGLEAM) study to investigate the genetic architecture of glaucoma in the Ohio Amish, which exhibits lower genetic and environmental heterogeneity compared to the general population. To date, we have enrolled 81 Amish individuals in our study from Holmes County, Ohio. As a part of our enrollment process, 62 GGLEAM study participants (42 glaucoma-affected and 20 unaffected individuals) received comprehensive eye examinations and glaucoma evaluations. Using the data from the Anabaptist Genealogy Database, we found that 80 of the GGLEAM study participants were related to one another through a large, multigenerational pedigree containing 1586 people. We plan to integrate the health and kinship data obtained for the GGLEAM study to interrogate glaucoma genetics and pathophysiology in this unique population.

Physical Activity Monitoring Using a Fitbit Device in Ischemic Stroke Patients: Prospective Cohort Feasibility Study.

BACKGROUND: Continuous tracking of ambulatory activity in real-world settings using step activity monitors has many potential uses. However, feasibility, accuracy, and correlation with performance measures in stroke patients have not been well-established. OBJECTIVE: The primary study objective was to determine adherence with wearing a consumer-grade step activity monitor, the Fitbit Charge HR, in home-going ischemic stroke patients during the first 90 days after hospital discharge. Secondary objectives were to (1) determine accuracy of step counts of the Fitbit Charge HR compared with a manual tally; (2) calculate correlations between the Fitbit step counts and the mobility performance scores at discharge and 30 days after stroke; (3) determine variability and change in weekly step counts over 90 days; and (4) evaluate patient experience with using the Fitbit Charge HR poststroke. METHODS: A total of 15 participants with recent mild ischemic stroke wore a Fitbit Charge HR for 90 days after discharge and completed 3 mobility performance tests from the National Institutes of Health Toolbox at discharge and Day 30: (1) Standing Balance Test, (2) 2-Minute Walk Endurance Test, and (3) 4-Meter Walk Gait Speed Test. Accuracy of step activity monitors was assessed by calculating differences in steps recorded on the step activity monitor and a manual tally during 2-minute walk tests. RESULTS: Participants had a mean age of 54 years and a median modified Rankin scale score of 1. Mean daily adherence with step activity monitor use was 83.6%. Mean daily step count in the first week after discharge was 4376. Daily step counts increased slightly during the first 30 days after discharge (average increase of 52.5 steps/day; 95% CI 32.2-71.8) and remained stable during the 30-90 day period after discharge. Mean step count difference between step activity monitor and manual tally was -4.8 steps (-1.8%). Intraclass correlation coefficients for step counts and 2-minute walk, standing balance, and 4-meter gait speed at discharge were 0.41 (95% CI -0.14 to 0.75), -0.12 (95% CI -0.67 to 0.64), and 0.17 (95% CI -0.46 to 0.66), respectively. Values were similarly poor at 30 days. CONCLUSIONS: The use of consumer-grade Fitbit Charge HR in patients with recent mild stroke is feasible with reasonable adherence and accuracy. There was poor correlation between step counts and gait speed, balance, and endurance. Further research is needed to evaluate the association between step counts and other outcomes relevant to patients, including patient-reported outcomes and measures of physical function.

Satisfaction with Care and Satisfaction with Decision Making are Similar Regardless of Staffing Model in a Neurocritical Care Unit.

INTRODUCTION: Patient-centered care, particularly shared medical decision making, is difficult to measure in critically ill patients where decisions are often made by a designated surrogate, often receiving information from multiple providers with varying degrees of training. The purpose of this study was to compare short-term satisfaction with care and decision making in patients or surrogates between two neurocritical care units [one staffed by a neurocritical care attending and advanced practice providers (APPs) and one staffed by a neurocritical care attending and resident/fellow trainees] using the Family Satisfaction in the ICU (FS-ICU) survey. METHODS: Over a 6-month period, the FS-ICU was administered on a tablet device to patients or surrogates at least 24 h after admission and stored on REDCap database. RESULTS: One hundred and thirty-four patients or surrogates completed the FS-ICU. The response rates were 59.97% and 46.58% in the APP and trainee units, respectively. There were no differences in patient age, sex, ventilator days or ICU length of stay. Overall, there were no differences in satisfaction with care or perceived shared medical making between the units. Respondents who identified their relationship with the patient as "other" (not a spouse, parent, nor a sibling) were less satisfied with care. Additionally, surrogates who identified as parents of the patient were more satisfied with degree of shared medical decision making. CONCLUSION: This study showed that: (1) collecting FS-ICU in a neurocritical care unit is feasible, (2) overall there is no difference in short-term satisfaction with care or shared decision making between a NICU staffed with trainees compared to one staffed with APPs, and (3) parents of patients have a higher short-term satisfaction with degree of shared medical decision making.

Statistical driver genes as a means to uncover missing heritability for age-related macular degeneration.

BACKGROUND: Age-related macular degeneration (AMD) is a progressive retinal disease contributing to blindness worldwide. Multiple estimates for AMD heritability (h2) exist; however, a substantial proportion of h2 is not attributable to known genomic loci. The International AMD Genomics Consortium (IAMDGC) gathered the largest dataset of advanced AMD (ADV) cases and controls available and identified 34 loci containing 52 independent risk variants defining known AMD h2. To better define AMD heterogeneity, we used Pathway Analysis by Randomization Incorporating Structure (PARIS) on the IAMDGC data and identified 8 statistical driver genes (SDGs), including 2 novel SDGs not discovered by the IAMDGC. We chose to further investigate these pathway-based risk genes and determine their contribution to ADV h2, as well as the differential ADV subtype h2. METHODS: We performed genomic-relatedness-based restricted maximum-likelihood (GREML) analyses on ADV, geographic atrophy (GA), and choroidal neovascularization (CNV) subtypes to investigate the h2 of genotyped variants on the full DNA array chip, 34 risk loci (n = 2758 common variants), 52 variants from the IAMDGC 2016 GWAS, and the 8 SDGs, specifically the novel 2 SDGs, PPARA and PLCG2. RESULTS: Via GREML, full chip h2 was 44.05% for ADV, 46.37% for GA, and 62.03% for CNV. The lead 52 variants' h2 (ADV: 14.52%, GA: 8.02%, CNV: 13.62%) and 34 loci h2 (ADV: 13.73%, GA: 8.81%, CNV: 12.89%) indicate that known variants contribute ~ 14% to ADV h2. SDG variants account for a small percentage of ADV, GA, and CNV heritability, but estimates based on the combination of SDGs and the 34 known loci are similar to those calculated for known loci alone. We identified modest epistatic interactions among variants in the 2 SDGs and the 52 IAMDGC variants, including modest interactions between variants in PPARA and PLCG2. CONCLUSIONS: Pathway analyses, which leverage biological relationships among genes in a pathway, may be useful in identifying additional loci that contribute to the heritability of complex disorders in a non-additive manner. Heritability analyses of these loci, especially amongst disease subtypes, may provide clues to the importance of specific genes to the genetic architecture of AMD.

Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression.

Glaucoma, a disease characterized by progressive optic nerve degeneration, can be prevented through timely diagnosis and treatment. We characterize optic nerve photographs of 67,040 UK Biobank participants and use a multitrait genetic model to identify risk loci for glaucoma. A glaucoma polygenic risk score (PRS) enables effective risk stratification in unselected glaucoma cases and modifies penetrance of the MYOC variant encoding p.Gln368Ter, the most common glaucoma-associated myocilin variant. In the unselected glaucoma population, individuals in the top PRS decile reach an absolute risk for glaucoma 10 years earlier than the bottom decile and are at 15-fold increased risk of developing advanced glaucoma (top 10% versus remaining 90%, odds ratio = 4.20). The PRS predicts glaucoma progression in prospectively monitored, early manifest glaucoma cases (P = 0.004) and surgical intervention in advanced disease (P = 3.6 × 10-6). This glaucoma PRS will facilitate the development of a personalized approach for earlier treatment of high-risk individuals, with less intensive monitoring and treatment being possible for lower-risk groups.

Frequency of ClinVar Pathogenic Variants in Chronic Kidney Disease Patients Surveyed for Return of Research Results at a Cleveland Public Hospital.

Return of results is not common in research settings as standards are not yet in place for what to return, how to return, and to whom. As a pioneer of large-scale of return of research results, the Precision Medicine Initiative Cohort now known of All of Us plans to return pharmacogenomic results and variants of clinical significance to its participants starting late 2019. To better understand the local landscape of possibilities regarding return of research results, we assessed the frequency of pathogenic variants and APOL1 renal risk variants in a small diverse cohort of chronic kidney disease patients (CKD) ascertained from a public hospital in Cleveland, Ohio genotyped on the Illumina Infinium MegaEX. Of the 23,720 ClinVar-designated variants directly assayed by the MegaEX, 8,355 (35%) had at least one alternate allele in the 130 participants genotyped. Of these, 18 ClinVar variants deemed pathogenic by multiple submitters with no conflicts in interpretation were distributed across 27 participants. The majority of these pathogenic ClinVar variants (14/18) were associated with autosomal recessive disorders. Of note were four African American carriers of TTR rs76992529 associated with amyloidogenic transthyretin amyloidosis, otherwise known as familial transthyretin amyloidosis (FTA). FTA, an autosomal dominant disorder with variable penetrance, is more common among African-descent populations compared with European-descent populations. Also common in this CKD population were APOL1 renal risk alleles G1 (rs73885319) and G2 (rs71785313) with 60% of the study population carrying at least one renal risk allele. Both pathogenic ClinVar variants and APOL1 renal risk alleles were distributed among participants who wanted actionable genetic results returned, wanted genetic results returned regardless of actionability, and wanted no results returned. Results from this local genetic study highlight challenges in which variants to report, how to interpret them, and the participant's potential for follow-up, only some of the challenges in return of research results likely facing larger studies such as All of Us.

Genetic Risk Scores.

Genome-wide variation data with millions of genetic markers have become commonplace. However, the potential for interpretation and application of these data for clinical assessment of outcomes of interest, and prediction of disease risk, is currently not fully realized. Many common complex diseases now have numerous, well-established risk loci and likely harbor many genetic determinants with effects too small to be detected at genome-wide levels of statistical significance. A simple and intuitive approach for converting genetic data to a predictive measure of disease susceptibility is to aggregate the effects of these loci into a single measure, the genetic risk score. Here, we describe some common methods and software packages for calculating genetic risk scores and polygenic risk scores, with focus on studies of common complex diseases. We review the basic information needed, as well as important considerations for constructing genetic risk scores, including specific requirements for phenotypic and genetic data, and limitations in their application. © 2019 by John Wiley & Sons, Inc.

Pathway Analysis Integrating Genome-Wide and Functional Data Identifies PLCG2 as a Candidate Gene for Age-Related Macular Degeneration.

Purpose: Age-related macular degeneration (AMD) is the worldwide leading cause of blindness among the elderly. Although genome-wide association studies (GWAS) have identified AMD risk variants, their roles in disease etiology are not well-characterized, and they only explain a portion of AMD heritability. Methods: We performed pathway analyses using summary statistics from the International AMD Genomics Consortium's 2016 GWAS and multiple pathway databases to identify biological pathways wherein genetic association signals for AMD may be aggregating. We determined which genes contributed most to significant pathway signals across the databases. We characterized these genes by constructing protein-protein interaction networks and performing motif analysis. Results: We determined that eight genes (C2, C3, LIPC, MICA, NOTCH4, PLCG2, PPARA, and RAD51B) "drive" the statistical signals observed across pathways curated in the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Ontology (GO) databases. We further refined our definition of statistical driver gene to identify PLCG2 as a candidate gene for AMD due to its significant gene-level signals (P < 0.0001) across KEGG, Reactome, GO, and NetPath pathways. Conclusions: We performed pathway analyses on the largest available collection of advanced AMD cases and controls in the world. Eight genes strongly contributed to significant pathways from the three larger databases, and one gene (PLCG2) was central to significant pathways from all four databases. This is, to our knowledge, the first study to identify PLCG2 as a candidate gene for AMD based solely on genetic burden. Our findings reinforce the utility of integrating in silico genetic and biological pathway data to investigate the genetic architecture of AMD.

Meta-analytic framework for modeling genetic coexpression dynamics.

Methods for exploring genetic interactions have been developed in an attempt to move beyond single gene analyses. Because biological molecules frequently participate in different processes under various cellular conditions, investigating the changes in gene coexpression patterns under various biological conditions could reveal important regulatory mechanisms. One of the methods for capturing gene coexpression dynamics, named liquid association (LA), quantifies the relationship where the coexpression between two genes is modulated by a third "coordinator" gene. This LA measure offers a natural framework for studying gene coexpression changes and has been applied increasingly to study regulatory networks among genes. With a wealth of publicly available gene expression data, there is a need to develop a meta-analytic framework for LA analysis. In this paper, we incorporated mixed effects when modeling correlation to account for between-studies heterogeneity. For statistical inference about LA, we developed a Markov chain Monte Carlo (MCMC) estimation procedure through a Bayesian hierarchical framework. We evaluated the proposed methods in a set of simulations and illustrated their use in two collections of experimental data sets. The first data set combined 10 pancreatic ductal adenocarcinoma gene expression studies to determine the role of possible coordinator gene USP9X in the Hippo pathway. The second experimental data set consisted of 907 gene expression microarray Escherichia coli experiments from multiple studies publicly available through the Many Microbe Microarray Database website (http://m3d.bu.edu/) and examined genes that coexpress with serA in the presence of coordinator gene Lrp.