Significant Genetic Variants Research Articles

Genetic variants are identified to increase risk of COVID-19 related mortality from UK Biobank data

BackgroundThe severity of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly heterogeneous. Studies have reported that males and some ethnic groups are at increased risk of death from COVID-19, which implies that individual risk of death might be influenced by host genetic factors.MethodsIn this project, we consider the mortality as the trait of interest and perform a genome-wide association study (GWAS) of data for 1778 infected cases (445 deaths, 25.03%) distributed by the UK Biobank. Traditional GWAS fails to identify any genome-wide significant genetic variants from this dataset. To enhance the power of GWAS and account for possible multi-loci interactions, we adopt the concept of super variant for the detection of genetic factors. A discovery-validation procedure is used for verifying the potential associations.ResultsWe find 8 super variants that are consistently identified across multiple replications as susceptibility loci for COVID-19 mortality. The identified risk factors on chromosomes 2, 6, 7, 8, 10, 16, and 17 contain genetic variants and genes related to cilia dysfunctions (DNAH7 and CLUAP1), cardiovascular diseases (DES and SPEG), thromboembolic disease (STXBP5), mitochondrial dysfunctions (TOMM7), and innate immune system (WSB1). It is noteworthy that DNAH7 has been reported recently as the most downregulated gene after infecting human bronchial epithelial cells with SARS-CoV-2.ConclusionsEight genetic variants are identified to significantly increase the risk of COVID-19 mortality among the patients with white British ancestry. These findings may provide timely clues and potential directions for better understanding the molecular pathogenesis of COVID-19 and the genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

Generalized correlation coefficient for genome-wide association analysis of cognitive ability in twins.

Despite a strong genetic background in cognitive function only a limited number of single nucleotide polymorphisms (SNPs) have been found in genome-wide association studies (GWASs). We hypothesize that this is partially due to mis-specified modeling concerning phenotype distribution as well as the relationship between SNP dosage and the level of the phenotype. To overcome these issues, we introduced an assumption-free method based on generalized correlation coefficient (GCC) in a GWAS of cognitive function in Danish and Chinese twins to compare its performance with traditional linear models. The GCC-based GWAS identified two significant SNPs in Danish samples (rs71419535, p = 1.47e-08; rs905838, p = 1.69e-08) and two significant SNPs in Chinese samples (rs2292999, p = 9.27e-10; rs17019635, p = 2.50e-09). In contrast, linear models failed to detect any genome-wide significant SNPs. The number of top significant genes overlapping between the two samples in the GCC-based GWAS was higher than when applying linear models. The GCC model identified significant genetic variants missed by conventional linear models, with more replicated genes and biological pathways related to cognitive function. Moreover, the GCC-based GWAS was robust in handling correlated samples like twin pairs. GCC is a useful statistical method for GWAS that complements traditional linear models for capturing genetic effects beyond the additive assumption.

Genetic and non-genetic factors associated with the phenotype of exceptional longevity & normal cognition

In this study, we split 2156 individuals from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) data into two groups, establishing a phenotype of exceptional longevity & normal cognition versus cognitive impairment. We conducted a genome-wide association study (GWAS) to identify significant genetic variants and biological pathways that are associated with cognitive impairment and used these results to construct polygenic risk scores. We elucidated the important and robust factors, both genetic and non-genetic, in predicting the phenotype, using several machine learning models. The GWAS identified 28 significant SNPs at p-value < 3 times 10^{-5} significance level and we pinpointed four genes, ESR1, PHB, RYR3, GRIK2, that are associated with the phenotype though immunological systems, brain function, metabolic pathways, inflammation and diet in the CLHLS cohort. Using both genetic and non-genetic factors, four machine learning models have close prediction results for the phenotype measured in Area Under the Curve: random forest (0.782), XGBoost (0.781), support vector machine with linear kernel (0.780), and ell _2 penalized logistic regression (0.780). The top four important and congruent features in predicting the phenotype identified by these four models are: polygenic risk score, sex, age, and education.

Association between genetic variants at chromosome 9p21 and risk of coronary artery disease in Emirati Type 2 Diabetes patients

BackgroundCoronary Artery Disease (CAD) is a complex multifactorial condition and the leading cause of death worldwide. Several Genome-Wide Association Studies (GWAS) have reported significant CAD susceptibility genetic variants around the region at chromosome 9p21. It has also been reported that the same region is associated with Type 2 Diabetes Mellitus (T2DM). However, the association of this region and CAD has not been investigated in the people of Arabian origin in the United Arab Emirates (UAE). CAD accounts for an alarming 30% of death in the country. In this study, five of the most reported genetic variants in region 9p21 were genotyped to assess their association with the incidence of CAD in Emirati patients with T2DM. MethodsThe study cohort included 969 unrelated Emirati nationals, comprising 450 healthy, 341 T2DM with no CAD complication, and 178 T2DM with CAD complication. Genotyping of single nucleotide polymorphism (SNPs) rs10757274, rs4977574, rs2383206, rs10757278 and rs1333049 were performed using qPCR. ResultsFindings from this study do not support the notion of a critical role for chromosome 9p21 locus as T2DM with CAD risk in the Emirati population. ConclusionGWAS will be required on a larger cohort of subjects of Arabian ancestry to identify variants that could be more specific to chronic diseases in Arabs.

SARS-CoV-2 Receptor and Renin-Angiotensin System Regulation: Impact of Genetics Variants in ACE2 Gene Impact of Genetics Variants in the ACE2 Gene in the Functional Receptor of SARS-CoV-2

The ACE2 has a physiological role in the regulation of the Renin-Angiotensin System. It is also described your function as a receptor for SARS-CoV-2 and other coronaviruses. Genetic variants in ACE2 are associated with cardiovascular diseases in different human populations and drug response. There is no direct evidence that mutations in ACE2 confer resistance to coronavirus spike protein binding. The evolutionary relationship between spike protein binding and ACE2 is complex. Significant genetic variants are present in ACE2, meanwhile, the evolutionary time of contact of the human ACE2 to the virus is short and, therefore, it did not suffer sufficient selective pressures to offer resistance to viral spike protein binding at the population level. More efforts are needed to identify genetic variants in human ACE2 and other genes, and, consequently, conducting case-control studies to validate these variants and their possible association with infection rates by SARS-CoV-2 and/or clinical outcome.

Basic epidemiological parameter values from data of real-world in mega-cities: the characteristics of COVID-19 in Beijing, China

BackgroundWith the spread of SARS-CoV-2 worldwide, understanding the basic epidemiological parameter values of COVID-19 from real-world data in mega-cities is essential for disease prevention and control.MethodsTo investigate the epidemiological parameters in SARS-CoV-2 infected cases in Beijing, we studied all confirmed cases and close contacts in Beijing from Jan 1st to Apr 3rd 2020. The epidemiological and virological characteristics of SARS-CoV-2 were analyzed.ResultsA total of 602 cases were positive for SARS-CoV-2, including 585 confirmed patients and 17 asymptomatic infections. The imported cases were mainly from Wuhan initially and then from abroad. Among 585 confirmed case-patients, the median age was 39 years old. The mean incubation period was 6.3 days. The secondary attack rate among households was higher than social contacts (15.6 vs 4.6%). The secondary attack rate of healthcare workers (HCWs) was higher than non-HCWs’ (7.3 vs 4.2%). The basic reproduction number was 2.0, and the average serial interval was 7.6 days. No significant genetic variant was identified.ConclusionsThe transmissibility of SARS-CoV-2 was relatively high, especially among households and from HCWs, which draws specific public health attention. So far, no evidence of widespread circulation of SARS-CoV-2 in communities in Beijing was found.

The genetics of rheumatoid arthritis.

RA is a chronic systemic inflammatory disease that primarily affects the small joints of the hands and feet, and results in a mean reduction in life expectancy of 3-10 years. RA is a multigene disorder with a substantial genetic component and a heritability estimate of 60%. Large-scale Genome-Wide Association Studies (GWAS) and meta-analyses have revealed common disease-associated variants in the population that may contribute cumulatively to RA pathogenesis. This review identifies the most significant genetic variants associated with RA susceptibility to date, with particular focus on the contribution of the HLA class II genes across different ethnic groups. Also discussed are the potential applications of pharmacogenomics to RA management by identifying polymorphisms associated with variation in treatment response or toxicity. The use of genetic variants to guide treatment strategy has the potential to not only reduce National Health Service costs, but also drastically improve patient experience and quality of life.

Use of multivariate factor analysis of detailed milk fatty acid profile to perform a genome-wide association study in Italian Simmental and Italian Holstein.

Milk fatty acid (FA) profile is a clear example of complex and multiple correlated traits whose genetic basis is difficult to assess. Although genome-wide association (GWA) studies have been successful in the identification of significant genetic variants for complex traits, when correlated phenotypes are analysed separately, the outcomes are difficult to compare and interpret in a metabolic context. Here, we performed a multivariate factor analysis (MFA) on Italian Simmental and Italian Holstein milk fat profiles to extract latent unobserved factors able to explain correlation structure and common metabolic function among different FAs. Individual factor scores obtained by MFA were used to perform a single-SNP based GWA. In both breeds, MFA was able to extract ten latent factors with specific biological meaning, notably: de novo synthesis, desaturation activity and biohydrogenation. The GWA result confirmed the increased power of joint association analysis on multiple correlated traits and allowed us to identify major candidate genes with well-documented function consistent with the metabolic classification of factors obtained, such as DGAT1, FASN and SCD.

Exclusive breastfeeding can attenuate body-mass-index increase among genetically susceptible children: A longitudinal study from the ALSPAC cohort.

Recent discoveries from large-scale genome-wide association studies (GWASs) explain a larger proportion of the genetic variability to BMI and obesity. The genetic risk associated with BMI and obesity can be assessed by an obesity-specific genetic risk score (GRS) constructed from genome-wide significant genetic variants. The aim of our study is to examine whether the duration and exclusivity of breastfeeding can attenuate BMI increase during childhood and adolescence due to genetic risks. A total sample of 5,266 children (2,690 boys and 2,576 girls) from the Avon Longitudinal Study of Parents and Children (ALSPAC) was used for the analysis. We evaluated the role of breastfeeding (exclusivity and duration) in modulating BMI increase attributed to the GRS from birth to 18 years of age. The GRS was composed of 69 variants associated with adult BMI and 25 non-overlapping SNPs associated with pediatric BMI. In the high genetic susceptible group (upper GRS quartile), exclusive breastfeeding (EBF) to 5 months reduces BMI by 1.14 kg/m2 (95% CI, 0.37 to 1.91, p = 0.0037) in 18-year-old boys, which compensates a 3.9-decile GRS increase. In 18-year-old girls, EBF to 5 months decreases BMI by 1.53 kg/m2 (95% CI, 0.76 to 2.29, p<0.0001), which compensates a 7.0-decile GRS increase. EBF acts early in life by delaying the age at adiposity peak and at adiposity rebound. EBF to 3 months or non-exclusive breastfeeding was associated with a significantly diminished impact on reducing BMI growth during childhood. EBF influences early life growth and development and thus may play a critical role in preventing overweight and obesity among children at high-risk due to genetic factors.

Hemizygous mutations in L1CAM in two unrelated male probands with childhood onset psychosis

To identify genes underlying childhood onset psychosis. Patients with onset of psychosis at age 13 or younger were identified from clinics across England, and they and their parents were exome sequenced and analysed for possible highly penetrant genetic contributors. We report two male childhood onset psychosis patients of different ancestries carrying hemizygous very rare possibly damaging missense variants (p.Arg846His and p.Pro145Ser) in the L1CAM gene. L1CAM is an X-linked Mendelian disease gene in which both missense and loss of function variants are associated with syndromic forms of intellectual disability and developmental disorder. This is the first study reporting a possible extension of the phenotype of L1CAM variant carriers to childhood onset psychosis. The family history and presence of other significant rare genetic variants in the patients suggest that there may be genetic interactions modulating the presentation.

Metabolite Genome-Wide Association Study (mGWAS) and Gene-Metabolite Interaction Network Analysis Reveal Potential Biomarkers for Feed Efficiency in Pigs.

Metabolites represent the ultimate response of biological systems, so metabolomics is considered the link between genotypes and phenotypes. Feed efficiency is one of the most important phenotypes in sustainable pig production and is the main breeding goal trait. We utilized metabolic and genomic datasets from a total of 108 pigs from our own previously published studies that involved 59 Duroc and 49 Landrace pigs with data on feed efficiency (residual feed intake (RFI)), genotype (PorcineSNP80 BeadChip) data, and metabolomic data (45 final metabolite datasets derived from LC-MS system). Utilizing these datasets, our main aim was to identify genetic variants (single-nucleotide polymorphisms (SNPs)) that affect 45 different metabolite concentrations in plasma collected at the start and end of the performance testing of pigs categorized as high or low in their feed efficiency (based on RFI values). Genome-wide significant genetic variants could be then used as potential genetic or biomarkers in breeding programs for feed efficiency. The other objective was to reveal the biochemical mechanisms underlying genetic variation for pigs’ feed efficiency. In order to achieve these objectives, we firstly conducted a metabolite genome-wide association study (mGWAS) based on mixed linear models and found 152 genome-wide significant SNPs (p-value < 1.06 × 10−6) in association with 17 metabolites that included 90 significant SNPs annotated to 52 genes. On chromosome one alone, 51 significant SNPs associated with isovalerylcarnitine and propionylcarnitine were found to be in strong linkage disequilibrium (LD). SNPs in strong LD annotated to FBXL4, and CCNC consisted of two haplotype blocks where three SNPs (ALGA0004000, ALGA0004041, and ALGA0004042) were in the intron regions of FBXL4 and CCNC. The interaction network revealed that CCNC and FBXL4 were linked by the hub gene N6AMT1 that was associated with isovalerylcarnitine and propionylcarnitine. Moreover, three metabolites (i.e., isovalerylcarnitine, propionylcarnitine, and pyruvic acid) were clustered in one group based on the low-high RFI pigs. This study performed a comprehensive metabolite-based genome-wide association study (GWAS) analysis for pigs with differences in feed efficiency and provided significant metabolites for which there is significant genetic variation as well as biological interaction networks. The identified metabolite genetic variants, genes, and networks in high versus low feed efficient pigs could be considered as potential genetic or biomarkers for feed efficiency.

Estimation and inference for the indirect effect in high-dimensional linear mediation models

Mediation analysis is difficult when the number of potential mediators is larger than the sample size. In this paper we propose new inference procedures for the indirect effect in the presence of high-dimensional mediators for linear mediation models. We develop methods for both incomplete mediation, where a direct effect may exist, and complete mediation, where the direct effect is known to be absent. We prove consistency and asymptotic normality of our indirect effect estimators. Under complete mediation, where the indirect effect is equivalent to the total effect, we further prove that our approach gives a more powerful test compared to directly testing for the total effect. We confirm our theoretical results in simulations, as well as in an integrative analysis of gene expression and genotype data from a pharmacogenomic study of drug response. We present a novel analysis of gene sets to understand the molecular mechanisms of drug response, and also identify a genome-wide significant noncoding genetic variant that cannot be detected using standard analysis methods.

PMU56 IMPACT OF FDA APPROVAL OF NEW AGENTS ON THERAPEUTIC OPTIONS FOR GENETIC VARIANTS IN PEDIATRIC TUMORS

Providing therapy tailored to an individual patient’s genetic makeup is a fundamental hope of precision medicine. This requires both identification of genetic features and available therapeutics. Joint Consensus Recommendations for genetic variant significance (Li, et al. J Mol Diagn, 2017) include availability of any FDA approved targeting agent, inclusion in treatment guidelines, and quality of evidence regarding prognostic or therapeutic outcomes. This analysis examines the impact of new FDA approved agents on the classification of most highly significant genetic variants in pediatric malignancies over time.

A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank.

BackgroundCommon types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK.MethodsA genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication.ResultsWe identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10−11. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10−10 for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10−8 for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively).ConclusionsWe have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.

ABCG2 rs2231142 variant in hyperuricemia is modified by SLC2A9 and SLC22A12 polymorphisms and cardiovascular risk factors in an elderly community-dwelling population

BackgroundThe ABCG2 rs2231142 single nucleotide polymorphism (SNP) is one of the most significant genetic variants associated with hyperuricemia (HUA) in Asian populations. However, the risk of ABCG2 rs2231142 variants for HUA could interact with other important HUA risk variants and cardiovascular factors. This study investigated the effects of the combined association among ABCG2 rs2231142 and multiple HUA genetic variants or cardiovascular risk factors on HUA risk and serum uric acid (sUA) levels in an elderly Chinese population.MethodsA total of 1206 participants over 65 years old were enrolled in this study. Physical and laboratory examinations were performed for all participants. The ABCG2 rs2231142, SLC2A9 rs3733591, and SLC22A12 rs893006 SNPs were assayed using a standardized protocol. Logistic regression analysis and liner regression were adjusted respectively to account for the association between ABCG2 rs2231142 and other genetic variants, as well as between cardiovascular risk factors and HUA risk and sUA levels.ResultsThe prevalence of HUA was 14.71% in the elderly community-dwelling population. The ABCG2 rs2231142 risk T allele was associated with HUA risk (odds ratio (OR) = 1.63, 95% confidence interval (CI): 1.27–2.11; p = 1.65 × 10− 4) and with increased sUA levels (Beta = 0.16, p = 6.75 × 10− 9) in the whole study population. Linear regression analysis showed that the mean sUA level increased linearly with the number of risk alleles of the three candidate genetic variants (Beta = 0.18, p = 1.94 × 10− 12) The joint effect of the ABCG2 rs2231142 T allele and cardiovascular risk factors (obesity, hypertension and dyslipidemia) was also associated with increased HUA risk and sUA levels. Each copy of the risk T allele was significantly associated with enhanced HUA risk in patients with hypertriglyceridemia (OR = 2.52, 95% CI: 1.33–4.60; p = 0.003) compared to controls.ConclusionOur findings reinforce the importance of the ABCG2 rs2231143 variant as a crucial genetic locus for HUA in Chinese populations and demonstrated the combined effects of multiple genetic risk variants and cardiovascular risk exposures on HUA risk and increased sUA level.

Genetic variants in migraine: a field synopsis and systematic re-analysis of meta-analyses

ObjectiveNumerous genetic variants from meta-analyses of observational studies and GWAS were reported to be associated with migraine susceptibility. However, due to the random errors in meta-analyses, the noteworthiness of the results showing statistically significant remains doubtful. Thus, we performed this field synopsis and re-analysis study to evaluate the noteworthiness using a Bayesian approach in hope of finding true associations.MethodsRelevant meta-analyses from observational studies and GWAS examining correlation between all genetic variants and migraine risk were included in our study by a PubMed search. Identification of noteworthy associations were analyzed by false-positive rate probability (FPRP) and Bayesian false discovery probability (BFDP). Using noteworthy variants, GO enrichment analysis were conducted through DAVID online tool. Then, the PPI network and hub genes were performed using STRING database and CytoHubba software.ResultsAs for 8 significant genetic variants from observational studies, none of which showed noteworthy at prior probability of 0.001. Out of 47 significant genetic variants in GWAS, 36 were noteworthy at prior probability of 0.000001 via FPRP or BFDP. We further found the pathways “positive regulation of cytosolic calcium ion concentration” and “inositol phosphate-mediated signaling” and hub genes including MEF2D, TSPAN2, PHACTR1, TRPM8 and PRDM16 related to migraine susceptibility.ConclusionHerein, we have identified several noteworthy variants for migraine susceptibility in this field synopsis. We hope these data would help identify novel genetic biomarkers and potential therapeutic target for migraine.

Validation and implementation of a modular targeted capture assay for the detection of clinically significant molecular oncology alterations

ObjectivesThe rapid discovery of clinically significant genetic variants has translated to next-generation sequencing assays becoming out-of-date by the time they are designed, validated, and implemented. UW-OncoPlex addresses this through the adoption of a modular panel capable of redesign as significant alterations are identified. We describe the validation of OncoPlex version 6 (OPXv6) for the detection of single nucleotide variants (SNVs), insertions and deletions (indels), copy number variants (CNVs), structural variants (SVs), microsatellite instability (MSI), and tumor mutational burden (TMB) in a panel of 340 genes. DesignOne hundred twelve samples with diverse diagnoses were comprised of formalin-fixed-paraffin-embedded tissue, fresh-frozen tissue, plasma, peripheral blood, bone marrow, saliva, and cell-line DNA. Libraries were prepared from genomic and cell-free DNA, hybridized to a custom panel of xGen Lockdown probes, and sequenced on Illumina platforms. Sequences were processed through a custom bioinformatics pipeline, and variant calls were compared to prior orthogonal clinical results. ResultsAccuracy was 99% for SNVs ≥5% allele frequency, 98% for indels, 97% for SVs, 99% for CNVs, 100% for MSI, and 100% for TMB (compared to previous OncoPlex versions). Library preparation turnaround time decreased by 40%, and sequencing quality improved with a 2.5-fold increase in average sequencing coverage and 4-fold increase in percent on-target. ConclusionsOPXv6 demonstrates improvements over prior UW-OncoPlex versions including reduced capture cost, improved sequencing quality, and decreased time to results. The modular capture probe design also provides a nimble laboratory response in addressing the expansions necessary to meet the needs of the continuously evolving field of molecular oncology.

Histocompatibility Complex Status and Mendelian Randomization Analysis in Unsolved Antibody Deficiency.

The pathogenesis in the majority of patients with common variable immunodeficiency (CVID), the most common symptomatic primary immunodeficiency, remains unknown. We aimed to compare the minor and major histocompatibility complex (MHC) markers as well as polygenic scores of common genetic variants between patients with monogenic CVID and without known genetic mutation detected. Monogenic patients were identified in a CVID cohort using whole exome sequencing. Computational full-resolution MHC typing and confirmatory PCR amplicon-based high-resolution typing were performed. Exome-wide polygenic scores were developed using significantly different variants and multi-variant Mendelian randomization (MR) analyses were used to test the causality of significant genetic variants on antibody levels and susceptibility to infectious diseases. Among 83 CVID patients (44.5% females), monogenic defects were found in 40 individuals. Evaluation of the remaining CVID patients without known genetic mutation detected showed 13 and 27 significantly associated MHC-class I and II alleles, respectively. The most significant partial haplotype linked with the unsolved CVID was W*01:01:01-DMA*01:01:01-DMB*01:03:01:02-TAP1*01:01:01 (P < 0.001), where carriers had a late onset of the disease, only infection clinical phenotype, a non-familial form of CVID, post-germinal center defects and a non-progressive form of their disease. Exclusion of monogenic diseases allowed MR analyses to identify significant genetic variants associated with bacterial infections and improved discrepancies observed in MR analyses of previous GWAS studies with low pleiotropy mainly for a lower respiratory infection, bacterial infection and Streptococcal infection. This is the first study on the full-resolution of minor and major MHC typing and polygenic scores on CVID patients and showed that exclusion of monogenic forms of the disease unraveled an independent role of MHC genes and common genetic variants in the pathogenesis of CVID.

Effect of genetic liability to migraine on coronary artery disease and atrial fibrillation: a Mendelian randomization study.

Observational studies have implicated migraine as a risk factor for coronary artery disease (CAD) and atrial fibrillation (AF); however, it is unclear whether migraine is causal in this relationship. Potential causality between genetically instrumented liability to migraine and cardiovascular disease outcomes was investigated using two-sample Mendelian randomization. The exposure comprised 35 independent, genome-wide significant genetic variants identified in the largest published genome-wide association studyof migraine (Ncases =59674/Ncontrols = 316078). The outcome datasets included genome-wide association studies of CAD (76014/264785), myocardial infarction (43676/128199), angina (10618/326065) and AF (60620/970216). Mendelian randomization estimates were calculated using inverse-variance weighted regression, and were further assessed with conventional Mendelian randomization sensitivity analyses. Evidence was found for a protective effect of migraine liability on CAD (odds ratio 0.86, 95% confidence interval 0.76-0.96, P=0.003), myocardial infarction (0.86, 0.74-0.96, P=0.01) and angina (0.86, 0.75-0.99, P=0.04), but not on AF (1.00, 0.95-1.05, P=0.88). Analyses by migraine subtype showed an effect of liability tomigraine without aura on CAD risk (0.91, 0.84-0.99, P=0.014), but not of migraine with aura (1.00, 0.97-1.03, P=0.89). Sensitivity analyses indicated minimal bias by horizontal pleiotropy, outliers, reverse causality or sample overlap. A potentially protective effect of genetically instrumented liability to migraine on CAD risk was identified. Mechanistic research investigating this link is warranted.

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness.

Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.