Lead Single Nucleotide Polymorphisms Research Articles

Adaptive and Innate Immunity Are Key Drivers of Age at Onset of Multiple Sclerosis.

Multiple sclerosis (MS) age at onset (AAO) is a clinical predictor of long-term disease outcomes, independent of disease duration. Little is known about the genetic and biological mechanisms underlying age of first symptoms. We conducted a genome-wide association study (GWAS) to investigate associations between individual genetic variation and the MS AAO phenotype. The study population was comprised participants with MS in 6 clinical trials: ADVANCE (N = 655; relapsing-remitting [RR] MS), ASCEND (N = 555; secondary-progressive [SP] MS), DECIDE (N = 1,017; RRMS), OPERA1 (N = 581; RRMS), OPERA2 (N = 577; RRMS), and ORATORIO (N = 529; primary-progressive [PP] MS). Altogether, 3,905 persons with MS of European ancestry were analyzed. GWAS were conducted for MS AAO in each trial using linear additive models controlling for sex and 10 principal components. Resultant summary statistics across the 6 trials were then meta-analyzed, for a total of 8.3 × 10-6 single nucleotide polymorphisms (SNPs) across all trials after quality control and filtering for heterogeneity. Gene-based tests of associations, pathway enrichment analyses, and Mendelian randomization analyses for select exposures were also performed. Four lead SNPs within 2 loci were identified (p < 5 × 10-8), including a) 3 SNPs in the major histocompatibility complex and their effects were independent of HLA-DRB1*15:01 and b) a LOC105375167 variant on chromosome 7. At the gene level, the top association was HLA-C (p = 1.2 × 10-7), which plays an important role in antiviral immunity. Functional annotation revealed the enrichment of pathways related to T-cell receptor signaling, autoimmunity, and the complement cascade. Mendelian randomization analyses suggested a link between both earlier age at puberty and shorter telomere length and earlier AAO, while there was no evidence for a role for either body mass index or vitamin D levels. Two genetic loci associated with MS AAO were identified, and functional annotation demonstrated an enrichment of genes involved in adaptive and complement immunity. There was also evidence supporting a link with age at puberty and telomere length. The findings suggest that AAO in MS is multifactorial, and the factors driving onset of symptoms overlap with those influencing MS risk.

OA01 Cluster medicine: the role of genetics for identifying shared biological pathways between rheumatoid arthritis and common comorbidities for targeting treatments

Abstract Background/Aims Rheumatoid arthritis (RA) is a chronic inflammatory disorder associated with significant pain and disability, as well as increased risk of comorbidities. These comorbidities, such as coronary artery disease, stroke, heart failure and type 2 diabetes, often form predictable clusters highlighting the importance of common disease mechanisms. Identifying these clusters, and the underlying shared mechanisms, is key to the concept of cluster medicine which aims to take a more systemic approach to treating comorbidity. It is hypothesised that inflammatory processes in RA promote the pathogenesis of these comorbid diseases, which typically occur at an earlier stage of life than in the general population. However, few studies have investigated the degree of shared genetic susceptibility implicated across these traits. The present study aimed to identify and characterise pleiotropic loci and shared biological pathways involved in the pathogenesis of RA and cardiometabolic disorders. Methods European-only GWAS summary statistics were collected for RA (seropositive, seronegative, and overall) and seven cardiometabolic traits, including ischemic stroke, any stroke, heart failure, coronary artery disease, hypertension, atrial fibrillation, and type 2 diabetes. Cross-trait linkage disequilibrium score regression was employed to estimate the degree of genetic correlation (rg) between all pairs of traits. Subset-based meta-analysis was performed using the R package ASSET to identify pleiotropic single nucleotide polymorphisms (SNPs). Pleiotropic SNPs were assigned to genes based on positional and eQTL mapping. Prioritised genes were tested for over-representation in functional categories and biological pathways in gene sets obtained from MsigDB and WikiPathways using the hypergeometric test loci. Gene mapping and enrichment analyses were conducted in FUMA. Results RA showed significant positive genetic correlation with all cardiometabolic traits, with the seronegative subtype showing greater correlation than the seropositive subtype. Correlations between RA and cardiometabolic phenotypes ranged from 0.11 - 0.38, the strongest of which was between seronegative RA and heart failure (rg = 0.38, P = 2.6e-07). A total of 67 lead SNPs were identified as potentially pleiotropic. Pleiotropic SNPs were mapped to genes including IL6R, PTPN11, ATXN2, PLCL1 and SOX6. Pathway enrichment analyses revealed that mapped genes were primarily involved in inflammatory signalling pathways, involving interleukins, TNF-α and interferon (gamma and alpha) response. Conclusion This study provides evidence for pleiotropy across RA and cardiometabolic traits, whereby inherited genetic variants predispose to aberrant cytokine signalling, thus conferring risk to multiple diseases where inflammation is a key driver of pathogenesis. Disclosure M. Stoves: None. M. Soomro: None. S. Zhao: None. D. Plant: None. A. Barton: None. J. Bowes: None.

Shared Genetic Determinants of Schizophrenia and Autism Spectrum Disorder Implicate Opposite Risk Patterns: A Genome-Wide Analysis of Common Variants.

The synaptic pruning hypothesis posits that schizophrenia (SCZ) and autism spectrum disorder (ASD) may represent opposite ends of neurodevelopmental disorders: individuals with ASD exhibit an overabundance of synapses and connections while SCZ was characterized by excessive pruning of synapses and a reduction. Given the strong genetic predisposition of both disorders, we propose a shared genetic component, with certain loci having differential regulatory impacts. Genome-Wide single nucleotide polymorphism (SNP) data of European descent from SCZ (N cases = 53386, N controls = 77258) and ASD (N cases = 18381, N controls = 27969) were analyzed. We used genetic correlation, bivariate causal mixture model, conditional false discovery rate method, colocalization, Transcriptome-Wide Association Study (TWAS), and Phenome-Wide Association Study (PheWAS) to investigate the genetic overlap and gene expression pattern. We found a positive genetic correlation between SCZ and ASD (rg = .26, SE = 0.01, P = 7.87e-14), with 11 genomic loci jointly influencing both conditions (conjFDR <0.05). Functional analysis highlights a significant enrichment of shared genes during early to mid-fetal developmental stages. A notable genetic region on chromosome 17q21.31 (lead SNP rs2696609) showed strong evidence of colocalization (PP.H4.abf = 0.85). This SNP rs2696609 is linked to many imaging-derived brain phenotypes. TWAS indicated opposing gene expression patterns (primarily pseudogenes and long noncoding RNAs [lncRNAs]) for ASD and SCZ in the 17q21.31 region and some genes (LRRC37A4P, LINC02210, and DND1P1) exhibit considerable variation in the cerebellum across the lifespan. Our findings support a shared genetic basis for SCZ and ASD. A common genetic variant, rs2696609, located in the Chr17q21.31 locus, may exert differential risk regulation on SCZ and ASD by altering brain structure. Future studies should focus on the role of pseudogenes, lncRNAs, and cerebellum in synaptic pruning and neurodevelopmental disorders.

Menarche-a journey into womanhood: age at menarche and health-related outcomes in East Asians.

Are there associations of age at menarche (AAM) with health-related outcomes in East Asians? AAM is associated with osteoporosis, Type 2 diabetes (T2D), glaucoma, and uterine fibroids, as demonstrated through observational studies, polygenic risk scores, genetic correlations, and Mendelian randomization (MR), with additional findings indicating a causal effect of BMI and T2D on earlier AAM. Puberty timing is linked to adult disease risk, but research predominantly focuses on European populations, with limited studies in other groups. We performed an AAM genome-wide association study (GWAS) with 57890 Han Taiwanese females and examined the association between AAM and 154 disease outcomes using the Taiwanese database. Additionally, we examined genetic correlations between AAM and 113 diseases and 67 phenotypes using Japanese GWAS summary statistics. We performed AAM GWAS and gene-based GWAS studies to obtain summary statistics and identify potential AAM-related genes. We applied phenotype, polygenic risk scores, and genetic correlation analyses of AAM to explore health-related outcomes, using multivariate regression and linkage disequilibrium score regression analyses. We also explored potential bidirectional causal relationships between AAM and related outcomes through univariable and multivariable MR analyses. Fifteen lead single-nucleotide polymorphisms and 24 distinct genes were associated with AAM in Taiwan. AAM was genetically associated with later menarche and menopause, greater height, increased osteoporosis risk, but lower BMI, and reduced risks of T2D, glaucoma, and uterine fibroids in East Asians. Bidirectional MR analyses indicated that higher BMI/T2D causally leads to earlier AAM. Our findings were specific to Han Taiwanese individuals, with genetic correlation analyses conducted in East Asians. Further research in other ethnic groups is necessary. Our study provides insights into the genetic architecture of AAM and its health-related outcomes in East Asians, highlighting causal links between BMI/T2D and earlier AAM, which may suggest potential prevention strategies for early puberty. The work was supported by China Medical University, Taiwan (CMU110-S-17, CMU110-S-24, CMU110-MF-49, CMU111-SR-158, CMU111-MF-105, CMU111-MF-21, CMU111-S-35, CMU112-SR-30, and CMU112-MF-101), the China Medical University Hospital, Taiwan (DMR-111-062, DMR-111-153, DMR-112-042, DMR-113-038, and DMR-113-103), and the Ministry of Science and Technology, Taiwan (MOST 111-2314-B-039-063-MY3, MOST 111-2314-B-039-064-MY3, MOST 111-2410-H-039-002-MY3, and NSTC 112-2813-C-039-036-B). The funders had no influence on the data collection, analyses, or conclusions of the study. No conflict of interests to declare. N/A.

Multivariate canonical correlation analysis identifies additional genetic variants for chronic kidney disease

Chronic kidney diseases (CKD) have genetic associations with kidney function. Univariate genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), two complementary kidney function markers. However, it is unknown whether additional SNPs for kidney function can be identified by multivariate statistical analysis. To address this, we applied canonical correlation analysis (CCA), a multivariate method, to two individual-level CKD genotype datasets, and metaCCA to two published GWAS summary statistics datasets. We identified SNPs previously associated with kidney function by published univariate GWASs with high replication rates, validating the metaCCA method. We then extended discovery and identified previously unreported lead SNPs for both kidney function markers, jointly. These showed expression quantitative trait loci (eQTL) colocalisation with genes having significant differential expression between CKD and healthy individuals. Several of these identified lead missense SNPs were predicted to have a functional impact, including in SLC14A2. We also identified previously unreported lead SNPs that showed significant correlation with both kidney function markers, jointly, in the European ancestry CKDGen, National Unified Renal Translational Research Enterprise (NURTuRE)-CKD and Salford Kidney Study (SKS) datasets. Of these, rs3094060 colocalised with FLOT1 gene expression and was significantly more common in CKD cases in both NURTURE-CKD and SKS, than in the general population. Overall, by using multivariate analysis by CCA, we identified additional SNPs and genes for both kidney function and CKD, that can be prioritised for further CKD analyses.

Genetic susceptibility to prostate cancer in Taiwan: A genome-wide association study.

We conducted the first genome-wide association study (GWAS) of prostate cancer (PCa) in Taiwan with 1844 cases and 80,709 controls. Thirteen independent single-nucleotide polymorphisms (SNPs) reached genome-wide significance (p < 5 × 10-8 ). Among these, three were distinct from previously identified loci: rs76072851 in CORO2B gene (15q23), odds ratio (OR) = 1.54, 95% confidence interval (CI), 1.36-1.76, p = 5.30 × 10-11 ; rs7837051, near two long noncoding RNA (lncRNA) genes, PRNCR1 and PCAT2 (8q24.21), OR = 1.41 (95% CI, 1.31-1.51), p = 8.77 × 10-21 ; and rs56339048, near an lncRNA gene, CASC8 (8q24.21), OR = 1.25 (95% CI, 1.16-1.35), p = 2.14 × 10-8 . We refined the lead SNPs for two previously identified SNPs in Taiwanese: rs13255059 (near CASC8), p = 9.02 × 10-43 , and rs1456315 (inside PRNCR1), p = 4.33 × 10-42 . We confirmed 35 out of 49 GWAS-identified East Asian PCa susceptibility SNPs. In addition, we identified twoSNPs more specific to Taiwanese than East Asians: rs34295433 in LAMC1 (1q25.3) and rs6853490 in PDLIM5 (4q22.3). A weighted genetic risk score (GRS) was developed using the 40 validated SNPs and the area under the receiver-operating characteristiccurvefor the GRS to predict PCa was 0.67 (95% CI, 0.63-0.71). These identified SNPs provide valuable insights into the molecular mechanisms of prostate carcinogenesis in Taiwan and underscore the significant role of genetic susceptibility in regional differences in PCa incidence.

SscNOVA: a semi-supervised convolutional neural network for predicting functional regulatory variants in autoimmune diseases.

Genome-wide association studies (GWAS) have identified thousands of variants in the human genome with autoimmune diseases. However, identifying functional regulatory variants associated with autoimmune diseases remains challenging, largely because of insufficient experimental validation data. We adopt the concept of semi-supervised learning by combining labeled and unlabeled data to develop a deep learning-based algorithm framework, sscNOVA, to predict functional regulatory variants in autoimmune diseases and analyze the functional characteristics of these regulatory variants. Compared to traditional supervised learning methods, our approach leverages more variants' data to explore the relationship between functional regulatory variants and autoimmune diseases. Based on the experimentally curated testing dataset and evaluation metrics, we find that sscNOVA outperforms other state-of-the-art methods. Furthermore, we illustrate that sscNOVA can help to improve the prioritization of functional regulatory variants from lead single-nucleotide polymorphisms and the proxy variants in autoimmune GWAS data.

Genome-wide association identifies novel ROP risk loci in a multiethnic cohort

We conducted a genome-wide association study (GWAS) in a multiethnic cohort of 920 at-risk infants for retinopathy of prematurity (ROP), a major cause of childhood blindness, identifying 1 locus at genome-wide significance level (p < 5×10-8) and 9 with significance of p < 5×10-6 for ROP ≥ stage 3. The most significant locus, rs2058019, reached genome-wide significance within the full multiethnic cohort (p = 4.96×10-9); Hispanic and European Ancestry infants driving the association. The lead single nucleotide polymorphism (SNP) falls in an intronic region within the Glioma-associated oncogene family zinc finger 3 (GLI3) gene. Relevance for GLI3 and other top-associated genes to human ocular disease was substantiated through in-silico extension analyses, genetic risk score analysis and expression profiling in human donor eye tissues. Thus, we identify a novel locus at GLI3 with relevance to retinal biology, supporting genetic susceptibilities for ROP risk with possible variability by race and ethnicity.

Metabolite-based genome-wide association studies enable the dissection ofthe genetic bases of flavonoids, betaine and spermidine in wolfberry (Lycium).

Wolfberry is a plant with medicinal and food values. However, its bioactive ingredients and the corresponding genetic bases have not been determined. Here, we de novo generated a chromosome-level genome assembly for wolfberry, yielding a genome sequence of ~1.77 Gb with contig N50 of 50.55 Mb and 39 224 predicted gene models. A variation map, using 307 re-sequenced accessions, was called based on this genome assembly. Furthermore, the fruit metabolome of these accessions was profiled using 563 annotated metabolites, which separated Lycium barbarum L. and non-L. barbarum L. The flavonoids, coumarins, alkaloids and nicotinic acid contents were higher in the former than in the latter. A metabolite-based genome-wide association study mapped 156 164 significant single nucleotide polymorphisms corresponding to 340 metabolites. This included 19 219 unique lead single nucleotide polymorphisms in 1517 significant association loci, of which three metabolites, flavonoids, betaine and spermidine, were highlighted. Two candidate genes, LbUGT (evm.TU.chr07.2692) and LbCHS (evm.TU.chr07.2738), with non-synonymous mutations, were associated with the flavonoids content. LbCHS is a structural gene that interacts with a nearby MYB transcription factor (evm.TU.chr07.2726) both in L. barbarum and L. ruthenicum. Thus, these three genes might be involved in the biosynthesis/metabolism of flavonoids. LbSSADH (evm.TU.chr09.627) was identified as possibly participating in betaine biosynthesis/metabolism. Four lycibarbarspermidines (E-G and O) were identified, and only the lycibarbarspermidines O content was higher in L. barbarum varieties than in non-L. barbarum varieties. The evm.TU.chr07.2680 gene associated with lycibarbarspermidines O was annotated as an acetyl-CoA-benzylalcohol acetyltransferase, suggesting that it is a candidate gene for spermidine biosynthesis. These results provide novel insights into the specific metabolite profile of non-L. barbarum L. and the genetic bases of flavonoids, betaine and spermidine biosynthesis/metabolism.

Artificial intelligence reveals brain aging patterns in 27,402 individuals without diagnosed cognitive impairment that are linked to genetics, biomedical measures, and cognitive decline

AbstractBackgroundUnderstanding heterogeneity of structural brain changes in aging may provide insights into susceptibility to neurodegenerative diseases. We characterize the genetics underlying brain structural heterogeneity within cognitively unimpaired (CU) individuals using data‐driven machine learning applied to a diverse dataset of 27,402 individuals from 11 neuroimaging studies from the iSTAGING consortium.MethodStructural brain morphologic patterns of CU individuals were independently examined in four decade‐long intervals spanning ages 45 to 85. Within each interval, Smile‐GAN (Yang et al., 2021) was trained on baseline anatomic and white matter hyperintensity (WMH) volumes. Smile‐GAN probability scores were used as phenotypes in genome‐wide association studies (GWAS). Specifically, we performed multiple linear regressions controlling for confounders (e.g., age) via Plink (Purcell et al., 2007). We observed longitudinal clustering stability across decades, so individuals from adjacent age groups were combined into broader age groups ([45,65), [65,85)) due to the large sample requirement of GWAS. Genomic loci, represented by the top leading single nucleotide polymorphisms (SNPs), were defined considering linkage disequilibrium. We investigated associations of SNPs with clinical traits and mapped them to genes using the GWAS Catalog (Buniello et al., 2019).ResultThree structural brain aging patterns, relative to resilient agers (A0), consistent across decades, emerged: A1, or ‘typical’ aging with low atrophy and WMHs, and two ‘advanced’ aging patterns, one showing elevated WMHs and modest atrophy (A2) and the other displaying severe, widespread atrophy and moderate WMH load (A3) (Figure 1). GWAS discovered eight and six genomic loci in [45,65) and [65,85) age groups, respectively (Table 1, Figure 2). The lead SNPs for A1 and A2 were previously associated with several cardiometabolic risk factors, WMHs, and regional brain volumes. Interestingly, rs4843552, previously associated with white matter microstructure and regional brain volumes, showed opposite effects for A1 (protection) and A2 (risk), consistent with the neuroimaging patterns. WDR41 in A3 group was previously associated with the age of Alzheimer’s disease onset (Herold et al., 2016).ConclusionReproducible neuroimaging patterns defined by regional atrophy and WMH burden were identified across CU individuals and demonstrated unique genetics. Further research is needed to elucidate the neuropathological pathways that mediate these relationships.

Concordant and antagonistic associations of genetic variants with Alzheimer’s disease and diabetes mellitus through blood glucose and body‐mass index

AbstractBackgroundMounting evidence suggests common etiologies of Alzheimer’s disease (AD) and diabetes mellitus (DM). Genetic mechanisms underlying the risks of AD and DM remain elusive.MethodWe used individual‐level data from four longitudinal studies,—the Atherosclerosis Risk in Communities study, Cardiovascular Health Study, Framingham Heart Study, and UK Biobank,—to examine causal mediation effects in the associations of single nucleotide polymorphisms (SNPs) with AD and DM. We selected 178 lead SNPs representing 74 previously identified AD‐ and/or DM‐associated loci on 20 chromosomes (excluding chromosomes 6 and 21). First, we used marginal structural models to perform a univariate mediation meta‐analysis considering AD or DM as an outcome and blood glucose (BG) or body mass index (BMI) measured before the onset of AD and DM as a mediator. Then, we utilized summary statistics from these univariate analyses to examine pleiotropic mediation effects on AD and DM using an omnibus test.ResultWe identified 56 SNPs in 26 loci on 12 chromosomes attaining p&lt;0.05 in the univariate mediation meta‐analyses and genome‐wide significance (p&lt;5×10−8) in the pleiotropic meta‐analysis of indirect effects on AD and DM through BG and BMI. BG and BMI mediated associations of 27 SNPs—14 loci on nine chromosomes; none in the APOE locus— and 33 SNPs—14 loci on eight chromosomes, including the APOE locus—, respectively. SNPs only from two of 26 loci on chromosomes 7p15.1 (JAZF1 gene) and 10q25.2 (TCF7L2 gene) showed pleiotropic effects through both BG and BMI. Directions of the mediation effects on AD and DM were the same for the same alleles through BG and the opposite through BMI. The exclusion of DM‐affected subjects explained mediation effects on AD through BG in all 14 loci. In contrast, this exclusion improved the significance of the mediation effects on AD through BMI also in all loci by decreasing p‐values 0.5 to 2 orders of magnitude.ConclusionMost of the identified genetic variants increase susceptibility to AD and DM through different mechanisms. The BG‐associated genetic mechanism is common for AD and DM, whereas the BMI‐related genetic mechanism mediates the AD and DM risks in an antagonistic manner.

Cross-disorder GWAS meta-analysis of endocannabinoid DNA variations in major depressive disorder, bipolar disorder, attention deficit hyperactivity disorder, autism spectrum disorder, and schizophrenia

The endocannabinoid system (ECS) is implicated in multiple mental disorders. In this study, we explored DNA variations in the ECS across major depressive disorder (MDD), bipolar disorder, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and schizophrenia by performing a cross-disorder genome-wide association study (GWAS) meta-analysis. We obtained six datasets from the Psychiatric Genomics Consortium containing GWAS summary statistics from European cohorts (284,023 cases and 508,515 controls). Effective sample size weighted meta-analysis was performed for 2241 single nucleotide polymorphisms (SNPs) pertaining to gene bodies of 33 endocannabinoid genes using METAL, where an overall z-statistic is calculated for each marker based on a weighted sum of individual statistics. Heterogeneity was examined with I2 and X2 tests. MAGMA gene-based analysis was also performed. We identified nine SNPs significantly associated with a change in risk of having a mental disorder. The lead SNP was rs12805732 (Gene: Diacylglycerol Lipase Alpha; DAGLA). Four SNPs had substantial heterogeneity (I2>60 %). DAGLA had the strongest association with disease risk in gene-based analysis. Our findings suggest that the ECS may be a shared pathway in mental disorders. Future studies validating these findings would contribute to the identification of biomarkers of disease risk across multiple mental disorders.

Identification of single nucleotide polymorphisms (SNPs) associated with chronic graft-versus-host disease in patients undergoing allogeneic hematopoietic cell transplantation

IntroductionChronic graft-versus-host disease (cGVHD) is a debilitating side effect of allogeneic hematopoietic cell transplantation (HCT), affecting the quality of life of patients. We used whole exome sequencing to identify candidate SNPs and complete a multi-marker gene-level analysis using a cohort of cGVHD( +) (N = 16) and cGVHD( −) (N = 66) HCT patients.MethodsSaliva samples were collected from HCT patients (N = 82) pre-conditioning in a multi-center study from March 2011 to May 2018. Exome sequencing was performed and FASTQ files were processed for sequence alignments. Significant SNPs were identified by logistic regression using PLINK2v3.7 and Fisher’s exact test. One cGVHD( −) patient sample was excluded from further analysis since no SNP was present in at least 10% of the sample population. The FUMA platform’s SNP2GENE was utilized to annotate SNPs and generate a MAGMA output. Chromatin state visualization of lead SNPs was completed using Epilogos tool. FUMA’s GENE2FUNC was used to obtain gene function and tissue expression from lead genomic loci.ResultsLogistic regression classified 986 SNPs associated with cGVHD( +). SNP2GENE returned three genomic risk loci, four lead SNPs, 48 candidate SNPs, seven candidate GWAS tagged SNPs, and four mapped genes. Fisher’s exact test identified significant homozygous genotypes of four lead SNPs (p < 0.05). GENE2FUNC analysis of multi-marker SNP sets identified one positional gene set including lead SNPs for KANK1 and KDM4C and two curated gene sets including lead SNPs for PTPRD, KDM4C, and/or KANK1.ConclusionsOur data suggest that SNPs in three genes located on chromosome 9 confer genetic susceptibility to cGVHD in HCT patients. These genes modulate STAT3 expression and phosphorylation in cancer pathogenesis. The findings may have implications in the modulation of pathways currently targeted by JAK inhibitors in cGVHD clinical trials.

TMEM132D and VIPR2 Polymorphisms as Genetic Risk Loci for Retinal Detachment: A Genome-Wide Association Study and Polygenic Risk Score Analysis.

Retinal detachment (RD) is a sight-threatening ocular disease caused by separation of the neurosensory retina from the underlying retinal pigment epithelium layer. Its genetic basis is unclear because of a limited amount of data. In this study, we aimed to identify genetic risk loci associated with RD in participants without diabetes mellitus and to construct a polygenic risk score (PRS) to predict the risk of RD. A genome-wide association study was conducted using data from the Taiwan Biobank to identify RD risk loci. A total of 1533 RD cases and 106,270 controls were recruited, all of whom were Han Chinese. Replication studies were performed using data from the UK Biobank and Biobank Japan. To construct the PRS, a traditional clumping and thresholding method was performed and validated by fivefold cross-validation. Two novel loci with significant associations were identified. These two genes were TMEM132D (lead single nucleotide polymorphism [SNP]: rs264498, adjusted-P = 7.18 × 10-9) and VIPR2 (lead SNP: rs3812305, adjusted-P = 8.38 × 10-9). The developed PRS was effective in discriminating individuals at high risk of RD with a dose-response relationship. The quartile with the highest risk had an odds ratio of 1244.748 compared to the lowest risk group (95% confidence interval, 175.174-8844.892). TMEM132D and VIPR2 polymorphisms are genetic candidates linked to RD in Han Chinese populations. Our proposed PRS was effective at discriminating high-risk from low-risk individuals.

Genome-wide association analysis of cystatin-C kidney function in continental Africa

Chronic kidney disease is becoming more prevalent in Africa, and its genetic determinants are poorly understood. Creatinine-based estimated glomerular filtration rate (eGFR) is commonly used to estimate kidney function, modelling the excretion of the endogenous biomarker (creatinine). However, eGFR based on creatinine has been shown to inadequately detect individuals with low kidney function in Sub-Saharan Africa, with eGFR based on cystatin-C (eGFRcys) exhibiting significantly superior performance. Therefore, we opted to conduct a GWAS for eGFRcys. Using the Uganda Genomic Resource, we performed a genome-wide association study (GWAS) of eGFRcys in 5877 Ugandans and evaluated replication in independent studies. Subsequently, putative causal variants were screened through Bayesian fine-mapping. Functional annotation of the GWAS loci was performed using Functional Mapping and Annotation (FUMA). Three independent lead single nucleotide polymorphisms (SNPs) (P-value <5×10-8 (based on likelihood ratio test (LRT))) were identified; rs59288815 (ANK3), rs4277141 (OR51B5) and rs911119 (CST3). From fine-mapping, rs59288815 and rs911119 each had a posterior probability of causality of >99%. The rs911119 SNP maps to the cystatin C gene and has been previously associated with eGFRcys among Europeans. With gene-set enrichment analyses of the olfactory receptor family 51 overlapping genes, we identified an association with the G-alpha-S signalling events. Our study found two previously unreported associated SNPs for eGFRcys in continental Africans (rs59288815 and rs4277141) and validated a previously well-established SNP (rs911119) for eGFRcys. The identified gene-set enrichment for the G-protein signalling pathways relates to the capacity of the kidney to readily adapt to an ever-changing environment. Additional GWASs are required to represent the diverse regions in Africa. Wellcome (220740/Z/20/Z).

Genome Wide Association Study of Neuropathic Ocular Pain

To conduct a genome-wide association study (GWAS) of individuals with neuropathic ocular pain (NOP) symptoms to identify genomic variants that may predispose to NOP development. Prospective study of individuals with NOP. Three hundred twenty-nine patients recruited from the Miami Veterans Affairs eye clinic. The Neuropathic Pain Symptom Inventory modified for the eye (NPSI-Eye) was completed to calculate a NPSI-Eye-Sub-Score (summed ratings of burning and wind sensitivity) as an indicator of NOP severity. A GWAS was performed for the NPSI-Eye-Sub-Score with a significance threshold of P<5× 10-8. A gene-based analysis was performed using the multimarker analysis of genomic annotation software (in the functional mapping and annotation of GWAS online platform). The 13 865 778 single nucleotide polymorphisms (SNPs) from our GWAS analysis were mapped to 10 834 protein coding genes, and significant genes were run through gene set enrichment analysis. Identification of SNPs and protein products that may be associated with the development of NOP. One hundred seventy-one SNPs reached a threshold of P<10-5, of which 10 SNPs reached the suggestive level of significance of P<5× 10-7 and 1 SNP met our genome-wide significance threshold of P<5×10-8. This lead SNP, rs140293404 (P=1.23×10-8), is an intronic variant found within gene ENSG00000287251 coding for transcript ENST00000662732.1. Rs140293404 is in linkage disequilibrium with exon variant rs7926353 (r2 > 0.8) within ENSG00000279046 coding for transcript ENST00000624288.1. The most significant genes from gene-based tests were matrix metalloproteinase-19 (MMP19) (P=1.12× 10-5), zinc finger RNA-binding motif and serine/arginine rich-1 (ZRSR1) (P=1.48× 10-4), CTC-487M23.8 (P=1.79× 10-4), receptor expression-enhancing protein-5 (REEP5) (P=2.36× 10-4), and signal recognition particle-19 (SRP19) (P=2.56× 10-4). From gene set enrichment analysis, the sensory perception (false discovery rate=6.57× 10-3) and olfactory signaling (false discovery rate=1.63× 10-2) pathways were enriched with the most significant genes. Our GWAS revealed genes with protein products that may impact sensory perception, lending biological plausibility to a role for SNPs identified by our GWAS in the development of NOP. A better understanding of the biological relevance of these genes and pathways in the pathophysiology associated with NOP may facilitate future novel mechanism-based treatments. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

1472-P: Polygenic Risk Score for Liver Fat Predicts Earlier Onset of Type 2 Diabetes in an East Asian Population

Liver, pancreas fat deposition and volume have been associated with type 2 diabetes (T2D) risk by Mendelian randomization study. However, it is unknown whether genetic variation in these traits impact on T2D onset, insulin resistance and drug use. We hypothesized that (1) genetic predisposition to smaller pancreas would be associated with earlier onset of T2D and earlier need for insulin; (2) genetic predisposition to higher pancreas and liver fat would be associated with greater insulin resistance, earlier onset of T2D and earlier need for insulin. This study utilized three Chinese cohorts of genotyped T2D patients in Hong Kong: Hong Kong Diabetes Register (HKDR, n=6011), Hong Kong Diabetes Biobank Phase 1 (HKDB-P1, n=6662) and Hong Kong Diabetes Biobank Phase 2 (HKDB-P2, n= 5899). We used lead SNPs (single nucleotide polymorphisms) associated with pancreas volume (13 SNPs), fat (7 SNPs) and liver fat (8 SNPs) from UK Biobank (n&amp;gt;32,000) to construct PRS (Polygenic risk score) in these cohorts. Linear regression models were employed to examine the associations between PRS and age of T2D onset and insulin resistance. Multivariable cox regression models were employed to examine association with time to insulin use. All models included age (except for age of T2D onset), sex and top 4 genetic principal components as covariates. To assess the confounding effects of BMI, we also performed BMI subgroup analysis by stratifying individuals into underweight, normal and overweight groups. Our analyses found that higher PRS for liver fat, but not pancreatic size or fat predicts earlier onset of T2D in HKDB-P1 (p&amp;lt;0.001, t=−3.43). The direction of association in HKDB-P2 was consistent though not significant. When stratified by BMI, higher PRS for liver fat predicts earlier onset of T2D in HKDB-P1 (p= 0.002, t=−3.14) and HKDB-P2 (p=0.029, t=−2.19) among the overweight group. Our results highlighted a PRS of liver fat as a potential biomarker for age of T2D onset, which needs further validation. Disclosure G.Yu: None. C.Huang: None. A.Luk: Research Support; Novo Nordisk, Boehringer-Ingelheim, Bayer Inc., Speaker's Bureau; Eli Lilly and Company. E.S.H.Lau: None. Hong kong diabetes biobank study group: n/a. R.C.Ma: Advisory Panel; AstraZeneca, Merck &amp; Co., Inc., Other Relationship; Bayer Inc., Boehringer-Ingelheim, Research Support; Tricida, Inc., Roche Diagnostics, Novo Nordisk. C.H.Tam: None. M.Shi: None. B.Fan: None. C.K.Lim: Stock/Shareholder; GemVCare Ltd. J.C.Chan: Board Member; Asia Diabetes Foundation, Consultant; Bayer Inc., Celltrion, Boehringer Ingelheim and Eli Lilly Alliance, Sanofi, Research Support; AstraZeneca, Servier Laboratories, Viatris Inc., Hua Medicine, Merck KGaA, Applied Therapeutics Inc., Lee Powder, Pfizer Inc., Speaker's Bureau; Novartis, Stock/Shareholder; GemVCare Ltd. M.N.Weedon: None. R.A.Oram: Consultant; Janssen Research &amp; Development, LLC, Research Support; Randox R &amp; D. Funding Research Grants Council of the Hong Kong Special Administrative Region (CU-R4012-18); Croucher Foundation

A shared genetic contribution to osteoarthritis and COVID-19 outcomes: a large-scale genome-wide cross-trait analysis.

Patients with osteoarthritis (OA) are exposed to an increased risk of adverse outcomes of COVID-19, and they tend to experience disruption in access to healthcare services and exercise facilities. However, a deep understanding of this comorbidity phenomenon and the underlying genetic architecture of the two diseases is still unclear. In this study, we aimed to untangle the relationship between OA and COVID-19 outcomes by conducting a large-scale genome-wide cross-trait analysis. Genetic correlation and causal relationships between OA and COVID-19 outcomes (critical COVID-19, COVID-19 hospitalization, and COVID-19 infection) were estimated by linkage disequilibrium score regression and Mendelian Randomization approaches. We further applied Multi-Trait Analysis of GWAS and colocalization analysis to identify putative functional genes associated with both OA and COVID-19 outcomes. Significant positive genetic correlations between OA susceptibility and both critical COVID-19 (rg=0.266, P=0.0097) and COVID-19 hospitalization (rg=0.361, P=0.0006) were detected. However, there was no evidence to support causal genetic relationships between OA and critical COVID-19 (OR=1.17[1.00-1.36], P=0.049) or OA and COVID-19 hospitalization OR=1.08[0.97-1.20], P=0.143). These results were robustly consistent after the removal of obesity-related single nucleotide polymorphisms (SNPs). Moreover, we identified a strong association signal located near the FYCO1 gene (lead SNPs: rs71325101 for critical COVID-19, Pmeta=1.02×10-34; rs13079478 for COVID-19 hospitalization, Pmeta=1.09×10-25). Our findings further confirmed the comorbidity of OA and COVID-19 severity, but indicate a non-causal impact of OA on COVID-19 outcomes. The study offers an instructive perspective that OA patients did not generate negative COVID-19 outcomes during the pandemic in a causal way. Further clinical guidance can be formulated to enhance the quality of self-management in vulnerable OA patients.

Genetic factors for differentiated thyroid cancer in French Polynesia: new candidate loci.

Populations of French Polynesia (FP), where France performed atmospheric tests between 1966 and 1974, experience a high incidence of differentiated thyroid cancer (DTC). However, up to now, no sufficiently large study of DTC genetic factors in this population has been performed to reach definitive conclusion. This research aimed to analyze the genetic factors of DTC risk among the native FP populations. We analyzed more than 300000 single nucleotide polymorphisms (SNPs) genotyped in 283 DTC cases and 418 matched controls born in FP, most being younger than 15 years old at the time of the first nuclear tests. We analyzed the genetic profile of our cohort to identify population subgroups. We then completed a genome-wide analysis study on the whole population. We identified a specific genetic structure in the FP population reflecting admixture from Asian and European populations. We identified three regions associated with increased DTC risk at 6q24.3, 10p12.2, and 17q21.32. The lead SNPs at these loci showed respective p-values of 1.66×10-7, 2.39×10-7, and 7.19×10-7 and corresponding odds ratios of 2.02, 1.89, and 2.37. Our study results suggest a role of the loci 6q24.3, 10p12.2 and 17q21.32 in DTC risk. However, a whole genome sequencing approach would be better suited to characterize these factors than genotyping with microarray chip designed for the Caucasian population. Moreover, the functional impact of these three new loci needs to be further explored and validated.

Identification of novel loci for flowering time in mungbean [Vigna radiata (L.) R. Wilczek] using genome-wide association study.

Flowering time is an important crop trait. Mungbean flowers do not flower simultaneously, leading to asynchronous pod maturity and laborious multiple harvests per individual plant. The genomic and genetic mechanisms of flowering in mungbean are largely unknown. This study sought to discover new quantitative trait loci (QTLs) for days to first flowering in mungbean using a genome-wide association study (GWAS). In total, 206 mungbean accessions collected from 20 countries were sequenced using genotyping by sequencing. A GWAS was conducted using 3,596 single nucleotide polymorphisms (SNPs) using TASSEL v5.2. Seven significant SNPs were associated with first flowering time. Based on the linkage disequilibrium (LD) decay distance, LD block was determined from upstream to downstream of each SNP up to 384kb. The lead SNP (Chr2_51229568) was located in the DFF2-2 locus. Syntenic analysis between mungbean and soybean revealed the DFF2-2 locus had collinearity with soybean genomic regions containing flowering-related QTLs on Gm13 and Gm20. Identification of flowering-related QTLs and SNPs is important for developing synchronous pod maturity and desirable flowering traits in mungbean.