Autosomal dominant macular dystrophy linked to a chromosome 17 tandem duplication.

Hereditary Macular Dystrophies (HMDs) are a genetically diverse group of disorders that cause central vision loss due to photoreceptor and retinal pigment epithelium (RPE) damage. We investigated a family with a presumed novel autosomal dominant HMD characterized by faint, hypopigmented RPE changes involving the central retina. Genome and RNA sequencing identified the disease-causing variant to be a 560 kilobase tandem duplication on chromosome 17 [NC_000017.10 (hg19): g.4012590_4573014dup], which led to the formation of a novel ZZEF1-ALOX15 fusion gene, that upregulates ALOX15. ALOX15 encodes a lipoxygenase involved in polyunsaturated fatty acid metabolism. Functional studies showed retinal disorganization, and photoreceptor and RPE damage following electroporation of the chimera transcript in mouse retina. Photoreceptor damage also occurred following electroporation with a native ALOX15 transcript but not with a near-null ALOX15 transcript. Affected patients' lymphoblasts demonstrated lower levels of ALOX15 substrates and an accumulation of neutral lipids. We implicated the fusion gene as the cause of this family's HMD, due to mis-localization and overexpression of ALOX15, driven by the ZZEF1 promoter. To our knowledge, this is the first reported instance of a fusion gene leading to HMD or inherited retinal dystrophy, highlighting the need to prioritize duplication analysis in unsolved retinal dystrophies.

Skin autofluorescence and cause-specific mortality in a population-based cohort.

We aimed to assess the association of SAF with cardiovascular mortality in the general population and the possible association between SAF with other disease-specific mortality rates. We evaluated 77,143 participants without known diabetes or cardiovascular disease. The cause of death was ascertained by the municipality database. The associations between SAF and all-cause mortality, cardiovascular mortality and cancer mortality were assessed with Cox proportional hazard analysis.After a median follow-up of 115 months, 1447 participants were deceased (1.9%). SAF and age-adjusted SAF-z score were higher in all mortality groups. Cox regression analysis revealed that the highest quartile of SAF was associated with increased odds of cardiovascular mortality, (HR) 12.6 (7.3-21.7) and after adjusting for age (HR 1.8 (1.0-3.2)). Significance was lost after additional adjustments for sex, smoking status, and BMI (HR 1.4 (0.8-2.5). For cancer-related mortality the highest quartile of SAF was associated with higher probability of mortality in all models (unadjusted HR 8.6 (6.6-11.3), adjusted for age HR 2.1 (1.6-2.8)), adjusted for age, sex, smoking status, and BMI HR 1.7 (1.3-2.4)). SAF is associated with all-cause mortality as well as cardiovascular and cancer-related mortality in the general population.

Glucagon-like-peptide 1 receptor agonism and attempted suicide: A Mendelian randomisation study to assess a potential causal association.

Glucagon-like-peptide 1 receptor agonists (GLP-1RA) have transformed type 2 diabetes (T2D) and obesity management. Multiple regulatory agencies are investigating reported associations between GLP1-RA and increased suicide attempts (SA), but observational data may be prone to confounding. Randomised control trials (RCT) of GLP-1RA were largely undertaken in people at lower risk of SA. Real-world data suggest semaglutide use associates with reduced suicidal ideation and depression but was under-powered to statistically assess risk of SA. Mendelian randomisation (MR) leverages genetic instrument(s) to infer potential causal association between an exposure and an outcome. We undertook MR using missense variants in the gene encoding GLP1R that improve glycemia, lower T2D risk and/or lower BMI, to investigate potential causal association between GLP-1RA and SA. In people of European ancestry, MR did not find evidence genetically proxied GLP1RA increased SA in a general population cohort: (rs10305492, exposure: HbA1c, odds ratio [OR] and 95% confidence interval [CI]: 1.38, 0.41-4.62, p = .60), (rs10305492, exposure: FG, OR 1.27, 0.52-3.13, p = .60) and (rs1042044, exposure BMI, OR 0.30, 0.06-1.48) with concordant results in a multi-ancestry SA case-control cohort. In conclusion, we did not find MR evidence that increased GLP-1RA impacts SA. This awaits confirmation with RCT and real-world data.

Better together against genetic heterogeneity: A sex-combined joint main and interaction analysis of 290 quantitative traits in the UK Biobank.

Genetic effects can be sex-specific, particularly for traits such as testosterone, a sex hormone. While sex-stratified analysis provides easily interpretable sex-specific effect size estimates, the presence of sex-differences in SNP effect implies a SNP×sex interaction. This suggests the usage of the often overlooked joint test, testing for an SNP's main and SNP×sex interaction effects simultaneously. Notably, even without individual-level data, the joint test statistic can be derived from sex-stratified summary statistics through an omnibus meta-analysis. Utilizing the available sex-stratified summary statistics of the UK Biobank, we performed such omnibus meta-analyses for 290 quantitative traits. Results revealed that this approach is robust to genetic effect heterogeneity and can outperform the traditional sex-stratified or sex-combined main effect-only tests. Therefore, we advocate using the omnibus meta-analysis that captures both the main and interaction effects. Subsequent sex-stratified analysis should be conducted for sex-specific effect size estimation and interpretation.

Analyses of potential causal contributors to increased waist/hip ratio-associated cardiometabolic disease: A combined and sex-stratified Mendelian randomization study.

BACKGROUND: Increased waist/hip ratio (WHR) contributes to type 2 diabetes, fatty liver, dyslipidaemia, hypertension and coronary artery disease, with potential sex-differential effects. Postulated mediators include increased lipid flux, branched-chain amino acids, glycine and glycoprotein acetyl, but their relative contributions and sex-specific impact on WHR-associated cardiometabolic disease (CMD) are not established. METHODS: We therefore undertook combined and sex-stratified Mendelian randomization (MR) to assess the relative causal contributions of these mediators to WHR-associated CMD using summary statistics from the largest genome-wide association studies in European ancestries. RESULTS: In sex-combined MR analyses, increased WHR significantly reduces high-density lipoprotein (beta = -0.416, SE = 0.029, p = 2.87E-47), increases triglyceride (beta = 0.431, SE = 0.029, p = 1.87E-50), type 2 diabetes (odds ratio = 2.747, SE = 0.09, p = 26E-23), coronary artery disease (odds ratio = 1.478, SE = 0.045, p = 6.96E-18), alanine transaminase (beta = 0.062, SE = 0.004, p = 6.88E-67), and systolic (beta = 0.134, SE = 0.022, p = 7.81E-10) and diastolic blood pressure (beta = 0.162, SE = 0.026, p = 5.38E-10). Adjustment for the mediators attenuated WHR's effects, but the associations remained significant with concordant results in females. In males, a similar pattern was seen, except after adjusting for the effect of the ratio of monounsaturated fatty acid to total free fatty acid, the potential causal effect of WHR was no longer significant: high-density lipoprotein (beta = -0.117, SE = 0.069, p = .09) and triglyceride (beta = 0.051, SE = 0.068, p = .459). CONCLUSIONS: MR suggests WHR increases the risk of CMD independent of these mediators, with the exception of dyslipidaemia in males, which is largely driven by the monounsaturated fatty acid to total free fatty acid ratio.

Canadian COVID-19 host genetics cohort replicates known severity associations.

The HostSeq initiative recruited 10,059 Canadians infected with SARS-CoV-2 between March 2020 and March 2023, obtained clinical information on their disease experience and whole genome sequenced (WGS) their DNA. We analyzed the WGS data for genetic contributors to severe COVID-19 (considering 3,499 hospitalized cases and 4,975 non-hospitalized after quality control). We investigated the evidence for replication of loci reported by the International Host Genetics Initiative (HGI); analyzed the X chromosome; conducted rare variant gene-based analysis and polygenic risk score testing. Population stratification was adjusted for using meta-analysis across ancestry groups. We replicated two loci identified by the HGI for COVID-19 severity: the LZTFL1/SLC6A20 locus on chromosome 3 and the FOXP4 locus on chromosome 6 (the latter with a variant significant at P < 5E-8). We found novel significant associations with MRAS and WDR89 in gene-based analyses, and constructed a polygenic risk score that explained 1.01% of the variance in severe COVID-19. This study provides independent evidence confirming the robustness of previously identified COVID-19 severity loci by the HGI and identifies novel genes for further investigation.

Statistical Learning of Large-Scale Genetic Data: How to Run a Genome-Wide Association Study of Gene-Expression Data Using the 1000 Genomes Project Data.

Teaching statistics through engaging applications to contemporary large-scale datasets is essential to attracting students to the field. To this end, we developed a hands-on, week-long workshop for senior high-school or junior undergraduate students, without prior knowledge in statistical genetics but with some basic knowledge in data science, to conduct their own genome-wide association study (GWAS). The GWAS was performed for open source gene expression data, using publicly available human genetics data. Assisted by a detailed instruction manual, students were able to obtain ∼1.4 million p-values from a real scientific study, within several days. This early motivation kept students engaged in learning the theories that support their results, including regression, data visualization, results interpretation, and large-scale multiple hypothesis testing. To further their learning motivation by emphasizing the personal connection to this type of data analysis, students were encouraged to make short presentations about how GWAS has provided insights into the genetic basis of diseases that are present in their friends or families. The appended open source, step-by-step instruction manual includes descriptions of the datasets used, the software needed, and results from the workshop. Additionally, scripts used in the workshop are archived on Github and Zenodo to further enhance reproducible research and training.

Comprehensive whole-genome analyses of the UK Biobank reveal significant sex differences in both genotype missingness and allele frequency on the X chromosome.

The UK Biobank is the most used dataset for genome-wide association studies (GWAS). GWAS of sex, essentially sex differences in minor allele frequencies (sdMAF), has identified autosomal SNPs with significant sdMAF, including in the UK Biobank, but the X chromosome was excluded. Our recent report identified multiple regions on the X chromosome with significant sdMAF, using short-read sequencing of other datasets. We performed a whole genome sdMAF analysis, with ~410 k white British individuals from the UK Biobank, using array genotyped, imputed or exome sequencing data. We observed marked sdMAF on the X chromosome, particularly at the boundaries between the pseudo-autosomal regions (PAR) and the non-PAR (NPR), as well as throughout the NPR, consistent with our earlier report. A small fraction of autosomal SNPs also showed significant sdMAF. Using the centrally imputed data, which relied mostly on low-coverage whole genome sequence, resulted in 2.1% of NPR SNPs with significant sdMAF. The whole exome sequencing also displays sdMAF on the X chromosome, including some NPR SNPs with heterozygous genotype calls in males. Genotyping, sequencing and imputation of X chromosomal SNPs requires further attention to ensure the integrity for downstream association analysis.

Erythritol as a Potential Causal Contributor to Cardiometabolic Disease: A Mendelian Randomization Study.

People with type 2 diabetes frequently use low-calorie sweeteners to manage glycemia and reduce caloric intake. Use of erythritol, a low-calorie sweetener, has increased recently. Higher circulating concentration associates with major cardiac events and metabolic disease in observational data, prompting some concern. As observational data may be prone to confounding and reverse causality, we undertook bidirectional Mendelian randomization (MR) to investigate potential causal associations between erythritol and coronary artery disease (CAD), BMI, waist-hip-ratio (WHR), and glycemic and renal traits in cohorts of European ancestry. Analyses were undertaken using instruments comprising genome-wide significant variants from three cohorts with erythritol measurement. Across instruments, we did not find supportive evidence that increased erythritol increases CAD (b = -0.033 ± 0.02, P = 0.14; b = 0.46 ± 0.37, P = 0.23). MR indicates erythritol may decrease BMI (b = -0.04 ± 0.018, P = 0.03; b = -0.04 ± 0.0085, P = 1.23 × 10-5; b = -0.083 ± 0.092, P = 0.036), with potential evidence from one instrument of increased BMI adjusted for WHR (b = 0.046 ± 0.022, P = 0.035). No evidence of causal association was found with other traits. In conclusion, we did not find supportive evidence from MR that erythritol increases cardiometabolic disease. These findings await confirmation in well-designed prospective studies.

A genome-wide association, polygenic risk score and sex study on opioid use disorder treatment outcomes.

Opioid use disorder continues to be a health concern with a high rate of opioid related deaths occurring worldwide. Medication Assisted Treatments (MAT) have been shown to reduce opioid withdrawal, cravings and opioid use, however variability exists in individual's treatment outcomes. Sex-specific differences have been reported in opioid use patterns, polysubstance use and health and social functioning. Candidate gene studies investigating methadone dose as an outcome have identified several candidate genes and only five genome-wide associations studies have been conducted for MAT outcomes. This study aimed to identify genetic variants associated with MAT outcomes through genome-wide association study (GWAS) and test the association between genetic variants previously associated with methadone dose through a polygenic risk score (PRS). Study outcomes include: continued opioid use, relapse, methadone dose and opioid overdose. No genome-wide significance SNPs or sex-specific results were identified. The PRS identified statistically significant results (p < 0.05) for the outcome of methadone dose (R2 = 3.45 × 10-3). No other PRS was statistically significant. This study provides evidence for association between a PRS and methadone dose. More research on the PRS to increase the variance explained is needed before it can be used as a tool to help identify a suitable methadone dose within this population.

Beyond apples and pears: sex-specific genetics of body fat percentage.

Introduction: Biological sex influences both overall adiposity and fat distribution. Further, testosterone and sex hormone binding globulin (SHBG) influence adiposity and metabolic function, with differential effects of testosterone in men and women. Here, we aimed to perform sex-stratified genome-wide association studies (GWAS) of body fat percentage (BFPAdj) (adjusting for testosterone and sex hormone binding globulin (SHBG)) to increase statistical power. Methods: GWAS were performed in white British individuals from the UK Biobank (157,937 males and 154,337 females). To avoid collider bias, loci associated with SHBG or testosterone were excluded. We investigated association of BFPAdj loci with high density cholesterol (HDL), triglyceride (TG), type 2 diabetes (T2D), coronary artery disease (CAD), and MRI-derived abdominal subcutaneous adipose tissue (ASAT), visceral adipose tissue (VAT) and gluteofemoral adipose tissue (GFAT) using publicly available data from large GWAS. We also performed 2-sample Mendelian Randomization (MR) using identified BFPAdj variants as instruments to investigate causal effect of BFPAdj on HDL, TG, T2D and CAD in males and females separately. Results: We identified 195 and 174 loci explaining 3.35% and 2.60% of the variation in BFPAdj in males and females, respectively at genome-wide significance (GWS, p<5x10-8). Although the direction of effect at these loci was generally concordant in males and females, only 38 loci were common to both sexes at GWS. Seven loci in males and ten loci in females have not been associated with any adiposity/cardiometabolic traits previously. BFPAdj loci generally did not associate with cardiometabolic traits; several had paradoxically beneficial cardiometabolic effects with favourable fat distribution. MR analyses did not find convincing supportive evidence that increased BFPAdj has deleterious cardiometabolic effects in either sex with highly significant heterogeneity. Conclusions: There was limited genetic overlap between BFPAdj in males and females at GWS. BFPAdj loci generally did not have adverse cardiometabolic effects which may reflect the effects of favourable fat distribution and cardiometabolic risk modulation by testosterone and SHBG.

GWAS for the composite traits of hematuria and albuminuria.

Our GWAS of hematuria in the UK Biobank identified 6 loci, some of which overlap with loci for albuminuria suggesting pleiotropy. Since clinical syndromes are often defined by combinations of traits, generating a combined phenotype can improve power to detect loci influencing multiple characteristics. Thus the composite trait of hematuria and albuminuria was chosen to enrich for glomerular pathologies. Cases had both hematuria defined by ICD codes and albuminuria defined as uACR > 3 mg/mmol. Controls had neither an ICD code for hematuria nor an uACR > 3 mg/mmol. 2429 cases and 343,509 controls from the UK Biobank were included. eGFR was lower in cases compared to controls, with the exception of the comparison in females using CKD-EPI after age adjustment. Variants at 4 loci met genome-wide significance with the following nearest genes: COL4A4, TRIM27, ETV1 and CUBN. TRIM27 is part of the extended MHC locus. All loci with the exception of ETV1 were replicated in the Geisinger MyCode cohort. The previous GWAS of hematuria reported COL4A3-COL4A4 variants and HLA-B*0801 within MHC, which is in linkage disequilibrium with the TRIM27 variant (D' = 0.59). TRIM27 is highly expressed in the tubules. Additional loci included a coding sequence variant in CUBN (p.Ala2914Val, MAF = 0.014 (A), p = 3.29E-8, OR = 2.09, 95% CI = 1.61-2.72). Overall, GWAS for the composite trait of hematuria and albuminuria identified 4 loci, 2 of which were not previously identified in a GWAS of hematuria.

The effect of ascertainment on penetrance estimates for rare variants: Implications for establishing pathogenicity and for genetic counselling.

Next-generation sequencing has led to an explosion of genetic findings for many rare diseases. However, most of the variants identified are very rare and were also identified in small pedigrees, which creates challenges in terms of penetrance estimation and translation into genetic counselling in the setting of cascade testing. We use simulations to show that for a rare (dominant) disorder where a variant is identified in a small number of small pedigrees, the penetrance estimate can both have large uncertainty and be drastically inflated, due to underlying ascertainment bias. We have developed PenEst, an app that allows users to investigate the phenomenon across ranges of parameter settings. We also illustrate robust ascertainment corrections via the LOD (logarithm of the odds) score, and recommend a LOD-based approach to assessing pathogenicity of rare variants in the presence of reduced penetrance.

Genetics of cannabis use in opioid use disorder: A genome-wide association and polygenic risk score study.

BACKGROUND: Individuals with an Opioid Use Disorder (OUD) have increased rates of cannabis use in comparison to the general population. Research on the short- and long-term impacts of cannabis use in OUD patients has been inconclusive. A genetic component may contribute to cannabis cravings. AIMS: Identify genetic variants associated with cannabis use through Genome-wide Association Study (GWAS) methods and investigate a Polygenic Risk Score (PRS). In addition, we aim to identify any sex differences in effect size for genetic variants reaching or nearing genome-wide significance in the GWAS. METHODS: The study outcomes of interest were: regular cannabis use (yes/no) (n = 2616), heaviness of cannabis use (n = 1293) and cannabis cravings (n = 836). Logistic and linear regressions were preformed, respectively, to test the association between genetic variants and each outcome, regular cannabis use and heaviness of cannabis use. GWAS summary statistics from a recent large meta-GWAS investigating cannabis use disorder were used to conduct PRS's. Findings are limited to a European ancestry sample. RESULTS: No genome-wide significant associations were found. Rs1813412 (chromosome 17) for regular cannabis use and rs62378502 (chromosome 5) for heaviness of cannabis use were approaching genome-wide significance. Both these SNPs were nominally significant (p<0.05) within males and females, however sex did not modify the association. The PRS identified statistically significant association with cannabis cravings. The variance explained by all PRSs were less than 1.02x10-2. CONCLUSION: This study provides promising results in understanding the genetic contribution to cannabis use in individuals living with OUD.

Characterization of direct and/or indirect genetic associations for multiple traits in longitudinal studies of disease progression.

When quantitative longitudinal traits are risk factors for disease progression and subject to random biological variation, joint model analysis of time-to-event and longitudinal traits can effectively identify direct and/or indirect genetic association of single nucleotide polymorphisms (SNPs) with time-to-event. We present a joint model that integrates: (1) a multivariate linear mixed model describing trajectories of multiple longitudinal traits as a function of time, SNP effects, and subject-specific random effects and (2) a frailty Cox survival model that depends on SNPs, longitudinal trajectory effects, and subject-specific frailty accounting for dependence among multiple time-to-event traits. Motivated by complex genetic architecture of type 1 diabetes complications (T1DC) observed in the Diabetes Control and Complications Trial (DCCT), we implement a 2-stage approach to inference with bootstrap joint covariance estimation and develop a hypothesis testing procedure to classify direct and/or indirect SNP association with each time-to-event trait. By realistic simulation study, we show that joint modeling of 2 time-to-T1DC (retinopathy and nephropathy) and 2 longitudinal risk factors (HbA1c and systolic blood pressure) reduces estimation bias in genetic effects and improves classification accuracy of direct and/or indirect SNP associations, compared to methods that ignore within-subject risk factor variability and dependence among longitudinal and time-to-event traits. Through DCCT data analysis, we demonstrate feasibility for candidate SNP modeling and quantify effects of sample size and Winner's curse bias on classification for 2 SNPs identified as having indirect associations with time-to-T1DC traits. Joint analysis of multiple longitudinal and multiple time-to-event traits provides insight into complex traits architecture.

Gut Microbiome Composition Is Associated With Future Onset of Crohn's Disease in Healthy First-Degree Relatives.

BACKGROUND & AIMS: The cause of Crohn's disease (CD) is unknown, but the current hypothesis is that microbial or environmental factors induce gut inflammation in genetically susceptible individuals, leading to chronic intestinal inflammation. Case-control studies of patients with CD have cataloged alterations in the gut microbiome composition; however, these studies fail to distinguish whether the altered gut microbiome composition is associated with initiation of CD or is the result of inflammation or drug treatment. METHODS: In this prospective cohort study, 3483 healthy first-degree relatives (FDRs) of patients with CD were recruited to identify the gut microbiome composition that precedes the onset of CD and to what extent this composition predicts the risk of developing CD. We applied a machine learning approach to the analysis of the gut microbiome composition (based on 16S ribosomal RNA sequencing) to define a microbial signature that associates with future development of CD. The performance of the model was assessed in an independent validation cohort. RESULTS: In the validation cohort, the microbiome risk score (MRS) model yielded a hazard ratio of 2.24 (95% confidence interval, 1.03-4.84; P = .04), using the median of the MRS from the discovery cohort as the threshold. The MRS demonstrated a temporal validity by capturing individuals that developed CD up to 5 years before disease onset (area under the curve > 0.65). The 5 most important taxa contributing to the MRS included Ruminococcus torques, Blautia, Colidextribacter, an uncultured genus-level group from Oscillospiraceae, and Roseburia. CONCLUSION: This study is the first to demonstrate that gut microbiome composition is associated with future onset of CD and suggests that gut microbiome is a contributor in the pathogenesis of CD.

eXclusionarY: 10 years later, where are the sex chromosomes in GWASs?

10 years ago, a detailed analysis showed that only 33% of genome-wide association study (GWAS) results included the X chromosome. Multiple recommendations were made to combat such exclusion. Here, we re-surveyed the research landscape to determine whether these earlier recommendations had been translated. Unfortunately, among the genome-wide summary statistics reported in 2021 in the NHGRI-EBI GWAS Catalog, only 25% provided results for the X chromosome and 3% for the Y chromosome, suggesting that the exclusion phenomenon not only persists but has also expanded into an exclusionary problem. Normalizing by physical length of the chromosome, the average number of studies published through November 2022 with genome-wide-significant findings on the X chromosome is ∼1 study/Mb. By contrast, it ranges from ∼6 to ∼16 studies/Mb for chromosomes 4 and 19, respectively. Compared with the autosomal growth rate of ∼0.086 studies/Mb/year over the last decade, studies of the X chromosome grew at less than one-seventh that rate, only ∼0.012 studies/Mb/year. Among the studies that reported significant associations on the X chromosome, we noted extreme heterogeneities in data analysis and reporting of results, suggesting the need for clear guidelines. Unsurprisingly, among the 430 scores sampled from the PolyGenic Score Catalog, 0% contained weights for sex chromosomal SNPs. To overcome the dearth of sex chromosome analyses, we provide five sets of recommendations and future directions. Finally, until the sex chromosomes are included in a whole-genome study, instead of GWASs, we propose such studies would more properly be referred to as "AWASs," meaning "autosome-wide scans."