Patterns of Gene Expression, Splicing, and Allele-Specific Expression Vary among Macular Tissues and Clinical Stages of Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is a leading cause of blindness, and elucidating its underlying disease mechanisms is vital to the development of appropriate therapeutics. We identified differentially expressed genes (DEGs) and differentially spliced genes (DSGs) across the clinical stages of AMD in disease-affected tissue, the macular retina pigment epithelium (RPE)/choroid and the macular neural retina within the same eye. We utilized 27 deeply phenotyped donor eyes (recovered within a 6 h postmortem interval time) from Caucasian donors (60-94 years) using a standardized published protocol. Significant findings were then validated in an independent set of well-characterized donor eyes (n = 85). There was limited overlap between DEGs and DSGs, suggesting distinct mechanisms at play in AMD pathophysiology. A greater number of previously reported AMD loci overlapped with DSGs compared to DEGs between disease states, and no DEG overlap with previously reported loci was found in the macular retina between disease states. Additionally, we explored allele-specific expression (ASE) in coding regions of previously reported AMD risk loci, uncovering a significant imbalance in C3 rs2230199 and CFH rs1061170 in the macular RPE/choroid for normal eyes and intermediate AMD (iAMD), and for CFH rs1061147 in the macular RPE/choroid for normal eyes and iAMD, and separately neovascular AMD (NEO). Only significant DEGs/DSGs from the macular RPE/choroid were found to overlap between disease states. STAT1, validated between the iAMD vs. normal comparison, and AGTPBP1, BBS5, CERKL, FGFBP2, KIFC3, RORα, and ZNF292, validated between the NEO vs. normal comparison, revealed an intricate regulatory network with transcription factors and miRNAs identifying potential upstream and downstream regulators. Findings regarding the complement genes C3 and CFH suggest that coding variants at these loci may influence AMD development via an imbalance of gene expression in a tissue-specific manner. Our study provides crucial insights into the multifaceted genomic underpinnings of AMD (i.e., tissue-specific gene expression changes, potential splice variation, and allelic imbalance), which may open new avenues for AMD diagnostics and therapies specific to iAMD and NEO.

Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK , GRB14 , and KIAA0825 as novel risk loci for Alzheimer's disease: the Alzheimer's Disease Genetics Consortium.

Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in non-European ancestry groups in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry GWAS dataset in the Alzheimer's Disease (AD) Genetics Consortium (ADGC) to test for novel shared and ancestry-specific AD susceptibility loci and evaluate underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6,728 African American, 8,899 Hispanic (HIS), and 3,232 East Asian individuals, performing within-ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. We identified 13 loci with cross-ancestry associations including known loci at/near CR1 , BIN1 , TREM2 , CD2AP , PTK2B , CLU , SHARPIN , MS4A6A , PICALM , ABCA7 , APOE and two novel loci not previously reported at 11p12 ( LRRC4C ) and 12q24.13 ( LHX5-AS1 ). Reflecting the power of diverse ancestry in GWAS, we observed the SHARPIN locus using 7.1% the sample size of the original discovering single-ancestry GWAS (n=788,989). We additionally identified three GWS ancestry-specific loci at/near ( PTPRK ( P =2.4×10 -8 ) and GRB14 ( P =1.7×10 -8 ) in HIS), and KIAA0825 ( P =2.9×10 -8 in NHW). Pathway analysis implicated multiple amyloid regulation pathways (strongest with P adjusted =1.6×10 -4 ) and the classical complement pathway ( P adjusted =1.3×10 -3 ). Genes at/near our novel loci have known roles in neuronal development ( LRRC4C, LHX5-AS1 , and PTPRK ) and insulin receptor activity regulation ( GRB14 ). These findings provide compelling support for using traditionally-underrepresented populations for gene discovery, even with smaller sample sizes.

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.

Association of OPRM1 Functional Coding Variant With Opioid Use Disorder: A Genome-Wide Association Study.

Importance: With the current opioid crisis, it is important to improve understanding of the biological mechanisms of opioid use disorder (OUD). Objectives: To detect genetic risk variants for OUD and determine genetic correlations and causal association with OUD and other traits. Design, Setting, and Participants: A genome-wide association study of electronic health record-defined OUD in the Million Veteran Program sample was conducted, comprising 8529 affected European American individuals and 71 200 opioid-exposed European American controls (defined by electronic health record trajectory analysis) and 4032 affected African American individuals and 26 029 opioid-exposed African American controls. Participants were enrolled from January 10, 2011, to May 21, 2018, with electronic health record data for OUD diagnosis from October 1, 1999, to February 7, 2018. Million Veteran Program results and additional OUD case-control genome-wide association study results from the Yale-Penn and Study of Addiction: Genetics and Environment samples were meta-analyzed (total numbers: European American individuals, 10 544 OUD cases and 72 163 opioid-exposed controls; African American individuals, 5212 cases and 26 876 controls). Data on Yale-Penn participants were collected from February 14, 1999, to April 1, 2017, and data on Study of Addiction: Genetics and Environment participants were collected from 1990 to 2007. The key result was replicated in 2 independent cohorts: proxy-phenotype buprenorphine treatment in the UK Biobank and newly genotyped Yale-Penn participants. Genetic correlations between OUD and other traits were tested, and mendelian randomization analysis was conducted to identify potential causal associations. Main Outcomes and Measures: Main outcomes were International Classification of Diseases, Ninth Revision-diagnosed OUD or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision-diagnosed OUD (Million Veteran Program), and DSM-IV-defined opioid dependence (Yale-Penn and Study of Addiction: Genetics and Environment). Results: A total of 114 759 individuals (101 016 men [88%]; mean [SD] age, 60.1 [12.8] years) were included. In 82 707 European American individuals, a functional coding variant (rs1799971, encoding Asn40Asp) in OPRM1 (µ-opioid receptor gene, the main biological target for opioid drugs; OMIM 600018) reached genome-wide significance (G allele: ß = -0.066 [SE = 0.012]; P = 1.51 × 10-8). The finding was replicated in 2 independent samples. Single-nucleotide polymorphism-based heritability of OUD was 11.3% (SE = 1.8%). Opioid use disorder was genetically correlated with 83 traits, including multiple substance use traits, psychiatric illnesses, cognitive performance, and others. Mendelian randomization analysis revealed the following associations with OUD: risk of tobacco smoking, depression, neuroticism, worry neuroticism subcluster, and cognitive performance. No genome-wide significant association was detected for African American individuals or in transpopulation meta-analysis. Conclusions and Relevance: This genome-wide meta-analysis identified a significant association of OUD with an OPRM1 variant, which was replicated in 2 independent samples. Post-genome-wide association study analysis revealed associated pleiotropic characteristics. Recruitment of additional individuals with OUD for future studies-especially those of non-European ancestry-is a crucial next step in identifying additional significant risk loci.

Genome-Wide Association Study of Opioid Cessation.

The United States is experiencing an epidemic of opioid use disorder (OUD) and overdose-related deaths. However, the genetic basis for the ability to discontinue opioid use has not been investigated. We performed a genome-wide association study (GWAS) of opioid cessation (defined as abstinence from illicit opioids for >1 year or <6 months before the interview date) in 1130 African American (AA) and 2919 European ancestry (EA) participants recruited for genetic studies of substance use disorders and who met lifetime Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5) criteria for OUD. Association tests performed separately within each ethnic group were combined by meta-analysis with results obtained from the Comorbidity and Trauma Study. Although there were no genome-wide significant associations, we found suggestive associations with nine independent loci, including three which are biologically relevant: rs4740988 in PTPRD (pAA + EA = 2.24 × 10-6), rs36098404 in MYOM2 (pEA = 2.24 × 10-6), and rs592026 in SNAP25-AS1 (pEA = 6.53 × 10-6). Significant pathways identified in persons of European ancestry (EA) are related to vitamin D metabolism (p = 3.79 × 10-2) and fibroblast growth factor (FGF) signaling (p = 2.39 × 10-2). UK Biobank traits including smoking and drinking cessation and chronic back pain were significantly associated with opioid cessation using GWAS-derived polygenic risk scores. These results provide evidence for genetic influences on opioid cessation, suggest genetic overlap with other relevant traits, and may indicate potential novel therapeutic targets for OUD.

Identifying factors associated with opioid cessation in a biracial sample using machine learning.

AIM: Racial disparities in opioid use disorder (OUD) management exist, however, and there is limited research on factors that influence opioid cessation in different population groups. METHODS: We employed multiple machine learning prediction algorithms least absolute shrinkage and selection operator, random forest, deep neural network, and support vector machine to assess factors associated with ceasing opioid use in a sample of 1,192 African Americans (AAs) and 2,557 individuals of European ancestry (EAs) who met Diagnostic and Statistical Manual of Mental Disorders, 5th Edition criteria for OUD. Values for nearly 4,000 variables reflecting demographics, alcohol and other drug use, general health, non-drug use behaviors, and diagnoses for other psychiatric disorders, were obtained for each participant from the Semi-Structured Assessment for Drug Dependence and Alcoholism, a detailed semi-structured interview. RESULTS: Support vector machine models performed marginally better on average than other machine learning methods with maximum prediction accuracies of 75.4% in AAs and 79.4% in EAs. Subsequent stepwise regression considered the 83 most highly ranked variables across all methods and models and identified less recent cocaine use (AAs: odds ratio (OR) = 1.82, P = 9.19 × 10-5; EAs: OR = 1.91, P = 3.30 × 10-15), shorter duration of opioid use (AAs: OR = 0.55, P = 5.78 × 10-6; EAs: OR = 0.69, P = 3.01 × 10-7), and older age (AAs: OR = 2.44, P = 1.41 × 10-12; EAs: OR = 2.00, P = 5.74 × 10-9) as the strongest independent predictors of opioid cessation in both AAs and EAs. Attending self-help groups for OUD was also an independent predictor (P < 0.05) in both population groups, while less gambling severity (OR = 0.80, P = 3.32 × 10-2) was specific to AAs and post-traumatic stress disorder recovery (OR = 1.93, P = 7.88 × 10-5), recent antisocial behaviors (OR = 0.64, P = 2.69 × 10-3), and atheism (OR = 1.45, P = 1.34 × 10-2) were specific to EAs. Factors related to drug use comprised about half of the significant independent predictors in both AAs and EAs, with other predictors related to non-drug use behaviors, psychiatric disorders, overall health, and demographics. CONCLUSIONS: These proof-of-concept findings provide avenues for hypothesis-driven analysis, and will lead to further research on strategies to improve OUD management in EAs and AAs.

Single Nucleotide Polymorphism Facilitated Down-Regulation of the Cohesin Stromal Antigen-1: Implications for Colorectal Cancer Racial Disparities.

The biological underpinnings for racial disparities in colorectal cancer (CRC) incidence remain to be elucidated. We have previously reported that the cohesin SA-1 down-regulation is an early event in colon carcinogenesis which is dramatically accentuated in African-Americans. In order to investigate the mechanism, we evaluated single nucleotide polymorphisms (SNPs) for association with SA-1-related outcomes followed by gene editing of candidate SNP. We observed that rs34149860 SNP was significantly associated with a lower colonic mucosal SA-1 expression and evaluation of public databases showed striking racial discordance. Given that the predicted SNP would alter miR-29b binding site, we used CRISPR knock-in in CRC cells and demonstrated that the SNP but not wild-type had profound alterations in SA-1 expression with miR-29b inhibitor. This is the first demonstration of high-order chromatin regulators as a modulator of racial differences, risk alteration with SNPs and finally specific modulation by microRNAs.

A 3-bp deletion in the HBS1L-MYB intergenic region on chromosome 6q23 is associated with HbF expression.

Fetal hemoglobin (HbF) is regulated as a multigenic trait. By genome-wide association study, we confirmed that HBS1L-MYB intergenic polymorphisms (HMIP) and BCL11A polymorphisms are highly associated with HbF in Chinese ß-thalassemia heterozygotes. In this population, the variance in HbF resulting from the HMIP is 13.5%; that resulting from the BCL11A polymorphism is 6.4%. To identify the functional variant in HMIP, we used 1000 Genomes Project data, single nucleotide polymorphism imputation, comparisons of association results across populations, potential transcription factor binding sites, and analysis of phylogenetic conservation. Based on these studies, a hitherto unreported association between HbF expression and a 3-bp deletion, between 135 460 326 and 135 460 328 bp on chromosome 6q23 was found. This 3-bp deletion is in complete linkage disequilibrium with rs9399137, which is the single nucleotide polymorphism in HMIP most significantly associated with HbF among Chinese, Europeans, and Africans. Chromatin immunoprecipitation assays confirmed erythropoiesis-related transcription factors binding to this region in K562 cells. Based on transient expression of a luciferase reporter plasmid, the DNA fragment encompassing the 3-bp deletion polymorphism has enhancer-like activity that is further augmented by the introduction of the 3-bp deletion. This 3-bp deletion polymorphism is probably the most significant functional motif accounting for HMIP modulation of HbF in all 3 populations.