Repeated application of noxious stimuli leads to a progressively increased pain perception; this temporal summation is enhanced in and predictive of clinical pain disorders. Its electrophysiological correlate is wind-up, in which dorsal horn spinal neurons increase their response to repeated nociceptor stimulation. To understand the genetic basis of temporal summation, we undertook a GWAS of wind-up in healthy human volunteers and found significant association with SLC8A3 encoding sodium-calcium exchanger type 3 (NCX3). NCX3 was expressed in mouse dorsal horn neurons, and mice lacking NCX3 showed normal, acute pain but hypersensitivity to the second phase of the formalin test and chronic constriction injury. Dorsal horn neurons lacking NCX3 showed increased intracellular calcium following repetitive stimulation, slowed calcium clearance, and increased wind-up. Moreover, virally mediated enhanced spinal expression of NCX3 reduced central sensitization. Our study highlights Ca2+ efflux as a pathway underlying temporal summation and persistent pain, which may be amenable to therapeutic targeting.
We report a genome-wide association study for facial features in >6,000 Latin Americans. We placed 106 landmarks on 2D frontal photographs using the cloud service platform Face++. After Procrustes superposition, genome-wide association testing was performed for 301 inter-landmark distances. We detected nominally significant association (P-value <5×10-8) for 42 genome regions. Of these, 9 regions have been previously reported in GWAS of facial features. In follow-up analyses, we replicated 26 of the 33 novel regions (in East Asians or Europeans). The replicated regions include 1q32.3, 3q21.1, 8p11.21, 10p11.1, and 22q12.1 all comprising strong candidate genes involved in craniofacial development. Furthermore, the 1q32.3 region shows evidence of introgression from archaic humans. These results provide novel biological insights into facial variation and establish that automatic landmarking of standard 2D photographs is a simple and informative approach for the genetic analysis of facial variation, suitable for the rapid analysis of large population samples.
Distance between gnathion to pronasal
Distance between right frontozygomathic suture to right palpebrale superious
Distance between right eyebrow lower left corner to right exocanthion
Distance between right alare to stomion2
Distance between right endocanthion to left endocanthion
Distance between right eyebrow upper left corner to labilae superious
Distance between left eyebrow lower right corner to right crista philtre
Distance between pronasal to stomion1
Distance between right eyebrow lower left corner to right nasal root contour
Distance between a landmark on face contour to right palpebrale inferious
Distance between left exocanthion to right crista philtre
Distance between right eyebrow lower left corner to right alare
Distance between subnasal to right endocanthion
Distance between right frontozygomathic suture to right eyebrow lower left corner
Distance between right alare to right endocanthion
Distance between right eyebrow lower left corner to right palpebrale superious
Distance between a landmark on face contour to right palpebrale superious
Distance between a landmark on face contour to subnasal
Distance between right eyebrow upper left corner to right eyebrow lower left corner
Distance between left suture frontozygomathic to right palpebrale superious
Distance between right alare to right palpebrale inferious
Distance between right frontotemporale to labiale inferious
Distance between right exocanthion to stomion1
Distance between left endocanthion to right cheilion
Distance between left eyebrow upper right corner to right nasal root contour
Distance between right nasal root contour to left nasal root contour
Distance between pronasal to right alare
Distance between nasion to right nasal root contour
Distance between labilae superious to stomion2
Distance between left eyebrow upper right corner to right palpebrale inferious
Distance between a landmark on face contour to right eyebrow upper left corner
Distance between right eyebrow upper left corner to right crista philtre
Distance between right eyebrow upper left corner to nasion
Distance between right frontotemporale to stomion2
Distance between right alare to right cheilion
Distance between left eyebrow upper right corner to right endocanthion
Distance between right frontozygomathic suture to right frontotemporale
Distance between subnasal to right crista philtre
Distance between left eyebrow lower right corner to right alare
Distance between right nasal root contour to right palpebrale superious
Distance between subnasal to right palpebrale inferious
Distance between pronasal to right exocanthion
Distance between right crista philtre to stomion2
Distance between stomion1 to stomion2
Distance between labilae superious to stomion1
Distance between left eyebrow upper right corner to right eyebrow lower left corner
Distance between left eyebrow lower right corner to right nasal root contour
Distance between nasion to right palpebrale superious
Distance between right alare to subnasal
Distance between left palpebrale inferious to right crista philtre
Distance between right endocanthion to right cheilion
Distance between right alare to labiale inferious
Distance between right alare to stomion1
Distance between right endocanthion to right palpebrale inferious
Distance between right eyebrow lower left corner to nasion
Distance between right alare to right palpebrale superious
Distance between gnathion to labilae superious
Distance between left eyebrow upper right corner to right cheilion
Distance between left frontotemporale to right eyebrow lower left corner
Distance between right exocanthion to labilae superious
Distance between a landmark on face contour to right frontozygomathic suture
Distance between right eyebrow lower left corner to labilae superious
Distance between left frontotemporale to right endocanthion
Distance between gnathion to stomion2
Distance between right eyebrow lower left corner to left eyebrow lower right corner
Distance between right nasal root contour to subnasal
Distance between subnasal to stomion1
Distance between a landmark on face contour to right endocanthion
Distance between right frontotemporale to right eyebrow upper left corner
Distance between a landmark on face contour to right exocanthion
Distance between right eyebrow upper left corner to right alare
Distance between pronasal to right endocanthion
Distance between gnathion to right crista philtre
Distance between left eyebrow upper right corner to right palpebrale superious
Distance between right eyebrow lower left corner to subnasal
Distance between right nasal root contour to right cheilion
Distance between right eyebrow lower left corner to stomion1
Distance between right eyebrow upper left corner to right nasal root contour
Distance between left eyebrow lower right corner to right cheilion
Distance between right alare to labilae superious
Distance between a landmark on face contour to stomion2
Distance between right eyebrow lower left corner to right endocanthion
Distance between right palpebrale superious to left endocanthion
Distance between right alare to right exocanthion
Distance between right palpebrale inferious to right cheilion
Distance between a landmark on face contour to right alare
Distance between right frontozygomathic suture to right endocanthion
Distance between two landmarks on face contour
Distance between a landmark on face contour to nasion
Distance between gnathion to nasion
Distance between right eyebrow upper left corner to left eyebrow upper right corner
Distance between left suture frontozygomathic to right nasal root contour
Distance between right eyebrow lower left corner to pronasal
Distance between right exocanthion to left endocanthion
Distance between stomion2 to labiale inferious
Distance between a landmark on face contour to right nasal root contour
Distance between right eyebrow upper left corner to pronasal
Distance between right eyebrow upper left corner to right cheilion
Distance between right frontotemporale to left eyebrow upper right corner
Distance between right exocanthion to right endocanthion
Distance between right eyebrow lower left corner to right cheilion
Distance between gnathion to right alare
Distance between right palpebrale superious to stomion1
Distance between left alare to right endocanthion
Distance between left frontotemporale to right exocanthion
Distance between subnasal to right palpebrale superious
Distance between right eyebrow upper left corner to right endocanthion
Distance between right nasal root contour to right endocanthion
Distance between a landmark on face contour to right eyebrow lower left corner
Distance between right eyebrow upper left corner to right exocanthion
Distance between right frontotemporale to right alare
Distance between left palpebrale superious to right palpebrale inferious
Distance between right alare to left alare
Distance between right exocanthion to right crista philtre
Distance between right frontotemporale to right eyebrow lower left corner
Distance between left eyebrow lower right corner to right palpebrale superious
Distance between left eyebrow lower right corner to right exocanthion
Distance between left nasal root contour to right endocanthion
Distance between left eyebrow upper right corner to right exocanthion
Distance between subnasal to stomion2
Distance between right eyebrow upper left corner to stomion1
Distance between left eyebrow lower right corner to right endocanthion
Distance between right exocanthion to right palpebrale inferious
Distance between subnasal to labilae superious
Distance between left eyebrow lower right corner to right palpebrale inferious
Distance between stomion1 to labiale inferious
Distance between right eyebrow lower left corner to right crista philtre
Distance between pronasal to labiale inferious
Distance between left endocanthion to right palpebrale inferious
Distance between nasion to right endocanthion
Distance between right nasal root contour to right palpebrale inferious
Distance between left eyebrow upper right corner to right alare
Distance between right exocanthion to right palpebrale superious
Distance between right palpebrale superious to left palpebrale superious
Distance between left eyebrow upper right corner to right crista philtre
Distance between pronasal to right palpebrale inferious
Distance between right frontozygomathic suture to right eyebrow upper left corner
Distance between right alare to right crista philtre
Distance between right eyebrow upper left corner to subnasal
Distance between left palpebrale inferious to right cheilion
AIMS: Left atrial (LA) volume and function impose significant impact on cardiovascular pathogenesis if compromised. We aimed at investigating the genetic architecture of LA volume and function using cardiac magnetic resonance imaging data. METHODS AND RESULTS: We used the UK Biobank, which is a large prospective population study with available phenotypic and genetic data. On a subset of 35 658 European individuals, we performed genome-wide association studies on five volumetric and functional LA variables, generated using a machine learning algorithm. In total, we identified 18 novel genetic loci, mapped to genes with known roles in cardiomyopathy (e.g. MYO18B, TTN, DSP, ANKRD1) and arrhythmia (e.g. TTN, CASQ2, MYO18B, C9orf3). We observed high genetic correlation between LA volume and function and stroke, which was most pronounced for LA passive emptying fraction (rg = 0.40, P = 4 × 10-6). To investigate whether the genetic risk of atrial fibrillation (AF) is associated with LA traits that precede overt AF, we produced a polygenetic risk score for AF. We found that polygenetic risk for AF is associated with increased LA volume and decreased LA function in participants without AF [LAmax 0.25 (mL/m2)/standard deviation (SD), 95% confidence interval (CI) (0.15; 0.36), P = 5.13 × 10-6; LAmin 0.21 (mL/m2)/SD, 95% CI (0.15; 0.28), P = 1.86 × 10-10; LA active emptying fraction -0.35%/SD, 95% CI (-0.43; -0.26), P = 3.14 × 10-14]. CONCLUSION: We report on 18 genetic loci associated with LA volume and function and show evidence for several plausible candidate genes important for LA structure.
BACKGROUND AND AIMS: Little is known about genetic factors that affect development of alcohol-related cirrhosis. We performed a genome-wide association study (GWAS) of samples from the United Kingdom Biobank (UKB) to identify polymorphisms associated with risk of alcohol-related liver disease. METHODS: We performed a GWAS of 35,839 participants in the UKB with high intake of alcohol against markers of hepatic fibrosis (FIB-4, APRI, and Forns index scores) and hepatocellular injury (levels of aminotransferases). Loci identified in the discovery analysis were tested for their association with alcohol-related cirrhosis in 3 separate European cohorts (phase 1 validation cohort; n=2545). Variants associated with alcohol-related cirrhosis in the validation at a false discovery rate of less than 20% were then directly genotyped in 2 additional European validation cohorts (phase 2 validation, n=2068). RESULTS: In the GWAS of the discovery cohort, we identified 50 independent risk loci with genome-wide significance (P < 5 × 10-8). Nine of these loci were significantly associated with alcohol-related cirrhosis in the phase 1 validation cohort; 6 of these 9 loci were significantly associated with alcohol-related cirrhosis in phase 2 validation cohort, at a false discovery rate below 5%. The loci included variants in the mitochondrial amidoxime reducing component 1 gene (MARC1) and the heterogeneous nuclear ribonucleoprotein U like 1 gene (HNRNPUL1). After we adjusted for age, sex, body mass index, and type-2 diabetes in the phase 2 validation cohort, the minor A allele of MARC1:rs2642438 was associated with reduced risk of alcohol-related cirrhosis (adjusted odds ratio, 0.76; P=.0027); conversely, the minor C allele of HNRNPUL1:rs15052 was associated with an increased risk of alcohol-related cirrhosis (adjusted odds ratio, 1.30; P=.020). CONCLUSIONS: In a GWAS of samples from the UKB, we identified and validated (in 5 European cohorts) single-nucleotide polymorphisms that affect risk of alcohol-related cirrhosis in opposite directions: the minor A allele in MARC1:rs2642438 decreases risk, whereas the minor C allele in HNRNPUL1:rs15052 increases risk.
Aspartate aminotransferase platelet ratio index in high alcohol intake
Alanine transaminase levels in high alcohol intake
Aspartate transaminase levels in high alcohol intake
Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
The genetic background of lupus nephritis (LN) has not been completely elucidated. We performed a case-only study of 2886 SLE patients, including 947 (33%) with LN. Renal biopsies were available from 396 patients. The discovery cohort (Sweden, n = 1091) and replication cohort 1 (US, n = 962) were genotyped on the Immunochip and replication cohort 2 (Denmark/Norway, n = 833) on a custom array. Patients with LN, proliferative nephritis, or LN with end-stage renal disease were compared with SLE without nephritis. Six loci were associated with LN (p < 1 × 10-4, NFKBIA, CACNA1S, ITGA1, BANK1, OR2Y, and ACER3) in the discovery cohort. Variants in BANK1 showed the strongest association with LN in replication cohort 1 (p = 9.5 × 10-4) and proliferative nephritis in a meta-analysis of discovery and replication cohort 1. There was a weak association between BANK1 and LN in replication cohort 2 (p = 0.052), and in the meta-analysis of all three cohorts the association was strengthened (p = 2.2 × 10-7). DNA methylation data in 180 LN patients demonstrated methylation quantitative trait loci (meQTL) effects between a CpG site and BANK1 variants. To conclude, we describe genetic variations in BANK1 associated with LN and evidence for genetic regulation of DNA methylation within the BANK1 locus. This indicates a role for BANK1 in LN pathogenesis.
BACKGROUND: Further exploration of the possible effects of vegetable intake on kidney function is warranted. OBJECTIVE: We aimed to study the causality of the association between vegetable intake and kidney function by implementing Mendelian randomization (MR) analysis. METHODS: This study comprised a cross-sectional dietary investigation using UK Biobank data and MR analysis. For the cross-sectional investigation, 432,732 participants aged 40-69 y from the UK Biobank cohort were included. Self-reported vegetable intake was the exposure, and the outcomes were the estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD). Next, we included 337,138 participants of white British ancestry in the UK Biobank, and a genome-wide association study (GWAS) was performed to generate a genetic instrument. For MR, we first performed polygenic score (PGS)-based 1-sample MR. In addition, 2-sample MR was performed with CKDGen GWAS for kidney function traits, and the inverse variance weighted method was the main MR method. RESULTS: Higher vegetable intake was cross-sectionally associated with a higher eGFR (per heaped tablespoon increase; β: 0.154; 95% CI: 0.144, 0.165) and lower odds of CKD (OR: 0.975; 95% CI: 0.968, 0.982). A PGS for vegetable intake was significantly associated with a higher eGFR [per ordinal category increase (0, 1-3, 4-6, ≥7 tablespoons per day); β: 4.435; 95% CI: 2.337, 6.533], but the association with CKD remained nonsignificant (OR: 0.468; 95% CI: 0.143, 1.535). In the 2-sample MR, the causal estimates indicated that a higher genetically predicted vegetable intake was associated with a higher eGFR (percent change; β: 3.071; 95% CI: 0.602, 0.560) but nonsignificantly associated with the risk of CKD (OR: 0.560; 95% CI: 0.289, 1.083) in the European ancestry data from the CKDGen. CONCLUSIONS: This study suggests that higher vegetable intake may have a causal effect on higher eGFRs in the European population.
BACKGROUND: Little is known about the association between genetic susceptibility and the severity of hand, foot, and mouth disease (HFMD) infected with coxsackievirus A6 (CV-A6). METHODS: Three hundred and sixty-four CV-A6 HFMD patients were enrolled, including 115 severe and 249 mild patients. A genome-wide association study (GWAS) was performed involving eight DNA pools of 115 severe and 115 mild CV-A6 HFMD patients pair-matched by age and gender. Differences in relative allele signal scores of SNPs in Illumina Human OmniZhongHua-8 BeadChips were compared between the two groups. The tag SNPS for potentially functional SNPs or their high linked SNPs were selected for individual genotyping in all 364 patients and assessed for their associations with severe CV-A6 HFMD using multivariable logistic regression analyses. RESULTS: The top 30 significant SNPs obtained from pooled DNA GWAS analysis were checked for biological functions and their high linkage disequilibrium (LD) SNPs. Four tag SNPs (rs1558206, rs6927647, rs9375728 and rs10879355) were selected for further individual genotyping in 364 CV-A6 patients. Only SNP rs10879355 was associated with severe CV-A6 HFMD, with CC genotype having a greater risk of severe illness than TT+TC genotypes (OR=2.48, 95%CI: 1.34, 4.56). SNP rs4290270 is in complete LD with rs10879355 in Chinese Han children. CONCLUSIONS: This is the first report that one potentially functional SNP rs4290270 in the TPH2 gene may be associated with the risk of severe CV-A6 HFMD.
CV-A6-associated hand, foot, and mouth disease (severe vs mild)
BACKGROUND: The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets. METHODS: In this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches). RESULTS: We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified 3 CpG sites spread across 3 proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to 1 polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease and between IL12B and Crohn's disease. CONCLUSIONS: Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.
interleukin 15 receptor subunit alpha levels
interleukin-18 receptor 1 levels
Interleukin-10 receptor B levels
Tumor necrosis factor beta levels
Matrix metalloproteinase levels
Monocyte chemoattractant protein-4 levels
Matrix metalloproteinase-10 levels
Cystatin D levels
CCL25 levels
Fibroblast growth factor 5 levels
CCL23 levels
Tumor necrosis factor ligand superfamily member 12 levels
The characterization of germline genetic variation affecting cancer risk, known as cancer predisposition, is fundamental to preventive and personalized medicine. Studies of genetic cancer predisposition typically identify significant genomic regions based on family-based cohorts or genome-wide association studies (GWAS). However, the results of such studies rarely provide biological insight or functional interpretation. In this study, we conducted a comprehensive analysis of cancer predisposition in the UK Biobank cohort using a new gene-based method for detecting protein-coding genes that are functionally interpretable. Specifically, we conducted proteome-wide association studies (PWAS) to identify genetic associations mediated by alterations to protein function. With PWAS, we identified 110 significant gene-cancer associations in 70 unique genomic regions across nine cancer types and pan-cancer. In 48 of the 110 PWAS associations (44%), estimated gene damage is associated with reduced rather than elevated cancer risk, suggesting a protective effect. Together with standard GWAS, we implicated 145 unique genomic loci with cancer risk. While most of these genomic regions are supported by external evidence, our results also highlight many novel loci. Based on the capacity of PWAS to detect non-additive genetic effects, we found that 46% of the PWAS-significant cancer regions exhibited exclusive recessive inheritance. These results highlight the importance of recessive genetic effects, without relying on familial studies. Finally, we show that many of the detected genes exert substantial cancer risk in the studied cohort determined by a quantitative functional description, suggesting their relevance for diagnosis and genetic consulting.
Shared genetic factors contribute to the high degree of comorbidity among externalizing problems (e.g. substance use and antisocial behavior). We leverage this common genetic etiology to identify genetic influences externalizing problems in participants from the Collaborative Study on the Genetics of Alcoholism (European ancestry = 7568; African ancestry = 3274). We performed a family-based genome-wide association study (GWAS) on externalizing scores derived from criterion counts of five DSM disorders (alcohol dependence, alcohol abuse, illicit drug dependence, illicit drug abuse, and either antisocial personality disorder or conduct disorder). We meta analyzed these results with a similar measure of externalizing in an independent sample, Spit for Science (combined sample N = 15,112). We did not discover any robust genome-wide significant signals. Polygenic scores derived from the ancestry-specific GWAS summary statistics predicted externalizing problems in an independent European ancestry sample, but not in those of African ancestry. However, these PRS were no longer significant after adjusting for multiple testing. Larger samples with deep phenotyping are necessary for the discovery of SNPs related to externalizing problems.
Prognostication in patients with chronic lymphocytic leukemia (CLL) is challenging due to heterogeneity in clinical course. We hypothesize that constitutional genetic variation affects disease progression and could aid prognostication. Pooling data from seven studies incorporating 842 cases identifies two genomic locations associated with time from diagnosis to treatment, including 10q26.13 (rs736456, hazard ratio (HR) = 1.78, 95% confidence interval (CI) = 1.47-2.15; P = 2.71 × 10-9) and 6p (rs3778076, HR = 1.99, 95% CI = 1.55-2.55; P = 5.08 × 10-8), which are particularly powerful prognostic markers in patients with early stage CLL otherwise characterized by low-risk features. Expression quantitative trait loci analysis identifies putative functional genes implicated in modulating B-cell receptor or innate immune responses, key pathways in CLL pathogenesis. In this work we identify rs736456 and rs3778076 as prognostic in CLL, demonstrating that disease progression is determined by constitutional genetic variation as well as known somatic drivers.
Chronic lymphocytic leukemia (time to first treatment)
Antiplatelet response to clopidogrel shows wide variation, and poor response is correlated with adverse clinical outcomes. CYP2C19 loss-of-function alleles play an important role in this response, but account for only a small proportion of variability in response to clopidogrel. An aim of the International Clopidogrel Pharmacogenomics Consortium (ICPC) is to identify other genetic determinants of clopidogrel pharmacodynamics and clinical response. A genomewide association study (GWAS) was performed using DNA from 2,750 European ancestry individuals, using adenosine diphosphate-induced platelet reactivity and major cardiovascular and cerebrovascular events as outcome parameters. GWAS for platelet reactivity revealed a strong signal for CYP2C19*2 (P value = 1.67e-33). After correction for CYP2C19*2 no other single-nucleotide polymorphism reached genomewide significance. GWAS for a combined clinical end point of cardiovascular death, myocardial infarction, or stroke (5.0% event rate), or a combined end point of cardiovascular death or myocardial infarction (4.7% event rate) showed no significant results, although in coronary artery disease, percutaneous coronary intervention, and acute coronary syndrome subgroups, mutations in SCOS5P1, CDC42BPA, and CTRAC1 showed genomewide significance (lowest P values: 1.07e-09, 4.53e-08, and 2.60e-10, respectively). CYP2C19*2 is the strongest genetic determinant of on-clopidogrel platelet reactivity. We identified three novel associations in clinical outcome subgroups, suggestive for each of these outcomes.
Cardiovascular death, myocardial infarction or stroke in response to clopidogrel treatment
Cardiovascular death or myocardial infarction in response to clopidogrel treatment
Stent thrombosis in response to clopidogrel treatment
Platelet reactivity in response to clopidogrel treatment
Circulating inflammatory markers are essential to human health and disease, and they are often dysregulated or malfunctioning in cancers as well as in cardiovascular, metabolic, immunologic and neuropsychiatric disorders. However, the genetic contribution to the physiological variation of levels of circulating inflammatory markers is largely unknown. Here we report the results of a genome-wide genetic study of blood concentration of ten cytokines, including the hitherto unexplored calcium-binding protein (S100B). The study leverages a unique sample of neonatal blood spots from 9,459 Danish subjects from the iPSYCH initiative. We estimate the SNP-heritability of marker levels as ranging from essentially zero for Erythropoietin (EPO) up to 73% for S100B. We identify and replicate 16 associated genomic regions (p < 5 x 10-9), of which four are novel. We show that the associated variants map to enhancer elements, suggesting a possible transcriptional effect of genomic variants on the cytokine levels. The identification of the genetic architecture underlying the basic levels of cytokines is likely to prompt studies investigating the relationship between cytokines and complex disease. Our results also suggest that the genetic architecture of cytokines is stable from neonatal to adult life.
Monocyte chemoattractant protein-1 levels
Vascular endothelial growth factor A levels
IgA levels
Interleukin-18 levels
C-reactive protein levels
Thymus and reactivation regulated chemokine levels
OBJECTIVE: Tofacitinib is an oral JAK inhibitor for the treatment of rheumatoid arthritis (RA), psoriatic arthritis, and ulcerative colitis, and has been previously investigated for psoriasis (PsO). This meta-analysis of genome-wide association studies (GWAS) was performed to identify genetic factors associated with increased risk/faster onset of herpes zoster (HZ) in subjects with RA or PsO receiving tofacitinib treatment, and to determine potential mechanisms that could be attributed to the varying rates of HZ across ethnicities. METHODS: In an ethnicity/indication-specific, trans-ethnic, trans-population meta-analysis of GWAS in subjects with RA or PsO from phase II, phase III, and long-term extension studies of tofacitinib, 8 million genetic variants were evaluated for their potential association with time to an HZ event and incidence of an HZ event (case versus control) with tofacitinib treatment, using Cox proportional hazard and logistic regression analyses, respectively. RESULTS: In total, 5,246 subjects were included (3,168 with RA and 2,078 with PsO). After adjustment for age, baseline absolute lymphocyte count, genetically defined ethnicity, and concomitant methotrexate use (in RA subjects only), 4 loci were significantly associated with faster onset of HZ in European subjects (P < 5 × 10-8 ), including a single-nucleotide polymorphism (SNP) near CD83 (frequency of risk allele ~2% in European subjects versus ~0.1% in East Asian subjects). In the trans-ethnic, trans-population meta-analysis, the CD83 SNP remained significant. Four additional significant loci were identified in the meta-analysis, among which a SNP near IL17RB was associated with faster onset of HZ (meta-analysis hazard ratio 3.6 [95% confidence interval 2.40-5.44], P = 7.6 × 10-10 ; frequency of risk allele ~12% in East Asian subjects versus <0.2% in European subjects). CONCLUSION: Genetic analysis of tofacitinib-treated subjects with RA or PsO identified multiple loci associated with increased HZ risk. Prevalent variants near the immune-relevant genes CD83 and IL17RB in European and East Asian populations, respectively, may contribute to risk of HZ in tofacitinib-treated subjects.
Response to tofacitinib treatment in rheumatoid arthritis (herpes zoster)
Response to tofacitinib treatment in rheumatoid arthritis (herpes zoster)(time to event)
Response to tofacitinib treatment (herpes zoster)
Response to tofacitinib treatment (herpes zoster)(time to event)
Response to tofacitinib treatment in psoriasis (herpes zoster)
Response to tofacitinib treatment in psoriasis (herpes zoster)(time to event)
Keratoconus is characterised by reduced rigidity of the cornea with distortion and focal thinning that causes blurred vision, however, the pathogenetic mechanisms are unknown. It can lead to severe visual morbidity in children and young adults and is a common indication for corneal transplantation worldwide. Here we report the first large scale genome-wide association study of keratoconus including 4,669 cases and 116,547 controls. We have identified significant association with 36 genomic loci that, for the first time, implicate both dysregulation of corneal collagen matrix integrity and cell differentiation pathways as primary disease-causing mechanisms. The results also suggest pleiotropy, with some disease mechanisms shared with other corneal diseases, such as Fuchs endothelial corneal dystrophy. The common variants associated with keratoconus explain 12.5% of the genetic variance, which shows potential for the future development of a diagnostic test to detect susceptibility to disease.
Despite growing public awareness of the adverse consequences of excessive sun exposure, modifying sun-seeking behavior is challenging because it appears to be driven by addictive mechanisms. This can have effects on health because sun exposure, although beneficial, when prolonged and repeated shows a causal relationship with skin cancer risk. Using data from 2,500 United Kingdom twins, we observed sun seeking to be significantly heritable (h2 ≥ 58%). In a GWAS meta-analysis of sun-seeking behavior in 261,915 subjects of European ancestry, we identified five GWAS-significant loci previously associated with addiction, behavioral and personality traits, cognitive function, and educational attainment and enriched for CNS gene expression: MIR2113 (P = 2.08 × 10-11), FAM76B/MTMR2/CEP57 (P = 3.70 × 10-9), CADM2 (P = 9.36 × 10-9), TMEM182 (P = 1.64 × 10-8), and PLCL1/LINC01923/SATB2 (P = 3.93 × 10-8). These findings imply that the behavior concerning UV exposure is complicated by a genetic predisposition shared with neuropsychological traits. This should be taken into consideration when designing awareness campaigns and may help improve people's attitudes toward sun exposure.
Age-related hearing impairment (ARHI) is the most common sensory disorder in older adults. We conducted a genome-wide association meta-analysis of 121,934 ARHI cases and 591,699 controls from Iceland and the UK. We identified 21 novel sequence variants, of which 13 are rare, under either additive or recessive models. Of special interest are a missense variant in LOXHD1 (MAF = 1.96%) and a tandem duplication in FBF1 covering 4 exons (MAF = 0.22%) associating with ARHI (OR = 3.7 for homozygotes, P = 1.7 × 10-22 and OR = 4.2 for heterozygotes, P = 5.7 × 10-27, respectively). We constructed an ARHI genetic risk score (GRS) using common variants and showed that a common variant GRS can identify individuals at risk comparable to carriers of rare high penetrance variants. Furthermore, we found that ARHI and tinnitus share genetic causes. This study sheds a new light on the genetic architecture of ARHI, through several rare variants in both Mendelian deafness genes and genes not previously linked to hearing.
Preeclampsia is a serious complication of pregnancy, affecting both maternal and fetal health. In genome-wide association meta-analysis of European and Central Asian mothers, we identify sequence variants that associate with preeclampsia in the maternal genome at ZNF831/20q13 and FTO/16q12. These are previously established variants for blood pressure (BP) and the FTO variant has also been associated with body mass index (BMI). Further analysis of BP variants establishes that variants at MECOM/3q26, FGF5/4q21 and SH2B3/12q24 also associate with preeclampsia through the maternal genome. We further show that a polygenic risk score for hypertension associates with preeclampsia. However, comparison with gestational hypertension indicates that additional factors modify the risk of preeclampsia.
BACKGROUND: Given the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients. METHODS: We performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP < 0.15). RESULTS: Evidence of associations with breast cancer-specific survival was observed in three patient subgroups, with variant rs5934618 in patients with grade 3 tumors (15-year-hazard ratio (HR) [95% confidence interval (CI)] 1.32 [1.20, 1.45], P = 1.4E-08, BFDP = 0.01, per G allele); variant rs4679741 in patients with ER-positive tumors treated with endocrine therapy (15-year-HR [95% CI] 1.18 [1.11, 1.26], P = 1.6E-07, BFDP = 0.09, per G allele); variants rs1106333 (15-year-HR [95% CI] 1.68 [1.39,2.03], P = 5.6E-08, BFDP = 0.12, per A allele) and rs78754389 (5-year-HR [95% CI] 1.79 [1.46,2.20], P = 1.7E-08, BFDP = 0.07, per A allele), in patients with ER-negative tumors treated with chemotherapy. CONCLUSIONS: We found evidence of four loci associated with breast cancer-specific survival within three patient subgroups. There was limited evidence for the existence of associations in other patient subgroups. However, the power for many subgroups is limited due to the low number of events. Even so, our results suggest that the impact of common germline genetic variants on breast cancer-specific survival might be limited.
5-year breast cancer-specific survival (ER negative treated with chemotherapy)
15-year breast cancer-specific survival (ER positive treated with endocrine therapy)
15-year breast cancer-specific survival (ER negative treated with chemotherapy)
15-year breast cancer-specific survival (treated with anthracyclines)
15-year breast cancer-specific survival (grade 3 tumor)
5-year breast cancer-specific survival (treated with tamoxifen)
15-year breast cancer-specific survival (ER positive, PR positive, and HER2 negative)
15-year breast cancer-specific survival (ER positive or PR positive, and HER2 negative treated with chemotherapy)