Pleiotropic Associations Research Articles

A comprehensive gene-centric pleiotropic association analysis for 14 psychiatric disorders with GWAS summary statistics.

BackgroundRecent genome-wide association studies (GWASs) have revealed the polygenic nature of psychiatric disorders and discovered a few of single-nucleotide polymorphisms (SNPs) associated with multiple psychiatric disorders. However, the extent and pattern of pleiotropy among distinct psychiatric disorders remain not completely clear.MethodsWe analyzed 14 psychiatric disorders using summary statistics available from the largest GWASs by far. We first applied the cross-trait linkage disequilibrium score regression (LDSC) to estimate genetic correlation between disorders. Then, we performed a gene-based pleiotropy analysis by first aggregating a set of SNP-level associations into a single gene-level association signal using MAGMA. From a methodological perspective, we viewed the identification of pleiotropic associations across the entire genome as a high-dimensional problem of composite null hypothesis testing and utilized a novel method called PLACO for pleiotropy mapping. We ultimately implemented functional analysis for identified pleiotropic genes and used Mendelian randomization for detecting causal association between these disorders.ResultsWe confirmed extensive genetic correlation among psychiatric disorders, based on which these disorders can be grouped into three diverse categories. We detected a large number of pleiotropic genes including 5884 associations and 2424 unique genes and found that differentially expressed pleiotropic genes were significantly enriched in pancreas, liver, heart, and brain, and that the biological process of these genes was remarkably enriched in regulating neurodevelopment, neurogenesis, and neuron differentiation, offering substantial evidence supporting the validity of identified pleiotropic loci. We further demonstrated that among all the identified pleiotropic genes there were 342 unique ones linked with 6353 drugs with drug-gene interaction which can be classified into distinct types including inhibitor, agonist, blocker, antagonist, and modulator. We also revealed causal associations among psychiatric disorders, indicating that genetic overlap and causality commonly drove the observed co-existence of these disorders.ConclusionsOur study is among the first large-scale effort to characterize gene-level pleiotropy among a greatly expanded set of psychiatric disorders and provides important insight into shared genetic etiology underlying these disorders. The findings would inform psychiatric nosology, identify potential neurobiological mechanisms predisposing to specific clinical presentations, and pave the way to effective drug targets for clinical treatment.

GWAS of stool frequency provides insights into gastrointestinal motility and irritable bowel syndrome

SummaryGut dysmotility is associated with constipation, diarrhea, and functional gastrointestinal disorders like irritable bowel syndrome (IBS), although its molecular underpinnings are poorly characterized. We studied stool frequency (defined by the number of bowel movements per day, based on questionnaire data) as a proxy for gut motility in a GWAS meta-analysis including 167,875 individuals from UK Biobank and four smaller population-based cohorts. We identify 14 loci associated with stool frequency (p ≤ 5.0 × 10−8). Gene set and pathway analyses detected enrichment for genes involved in neurotransmitter/neuropeptide signaling and preferentially expressed in enteric motor neurons controlling peristalsis. PheWAS identified pleiotropic associations with dysmotility syndromes and the response to their pharmacological treatment. The genetic architecture of stool frequency correlates with that of IBS, and UK Biobank participants from the top 1% of stool frequency polygenic score distribution were associated with 5× higher risk of IBS with diarrhea. These findings pave the way for the identification of actionable pathological mechanisms in IBS and the dysmotility syndromes.

Quantitative and population genomics suggest a broad role of stay-green loci in the drought adaptation of sorghum.

Drought is a major constraint on plant productivity globally. Sorghum [Sorghum bicolor (L.) Moench] landraces have evolved in drought-prone regions, but the genetics of their adaptation is poorly understood. Here we sought to identify novel drought-tolerance loci and test hypotheses on the role of known loci including those underlying stay-green (Stg) postflowering drought tolerance. We phenotyped 590 diverse sorghum accessions from West Africa in 10 environments, under field-based managed drought stress [preflowering water stress (WS1), postflowering water stress (WS2), and well-watered (WW)] and rainfed (RF) conditions over 4 yr. Days to 50% flowering (DFLo), aboveground dry biomass (DBM), plant height (PH), and plant grain yield components (including grain weight [GrW], panicle weight [PW] and grain number [GrN] per plant, and 1000-grain weight [TGrW]) were measured, and genome-wide association studies (GWAS) was conducted. Broad-sense heritability for biomass and plant grain yield was high (33-92%) across environments. There was a significant correlation between stress tolerance index (STI) for GrW per plant across WS1 and WS2. Genome-wide association studies revealed that SbZfl1 and SbCN12, orthologs of maize (Zea mays L.) flowering genes, likely underlie flowering time variation under these conditions. Genome-wide association studies further identified associations (n = 134; common between two GWAS models) for STI and drought effects on plant yield components including 16 putative pleiotropic associations. Thirty of the associations colocalized with Stg1, Stg2, Stg3, and Stg4 loci and had large effects. Seven lead associations, including some within Stg1, overlapped with positive selection outliers. Our findings reveal previously undescribed natural genetic variation for drought-tolerance-related traits and suggest a broad role of Stg loci in drought adaptation of sorghum.

Pleiotropic predisposition to Alzheimer's disease and educational attainment: insights from the summary statistics analysis.

Epidemiological studies report beneficial associations of higher educational attainment (EDU) with Alzheimer’s disease (AD). Prior genome-wide association studies (GWAS) also reported variants associated with AD and EDU separately. The analysis of pleiotropic associations with these phenotypes may shed light on EDU-related protection against AD. We performed pleiotropic meta-analyses using Fisher’s method and omnibus test applied to summary statistics for single nucleotide polymorphisms (SNPs) associated with AD and EDU in large-scale univariate GWAS at suggestive-effect (5 × 10−8 < p < 0.1) and genome-wide (p ≤ 5 × 10−8) significance levels. We report 53 SNPs that attained p ≤ 5 × 10−8 at least in one of the pleiotropic meta-analyses and were reported in the univariate GWAS at 5 × 10−8 < p < 0.1. Of them, there were 46 pleiotropic SNPs according to Fisher’s method. Additionally, Fisher’s method identified 25 of 206 SNPs with pleiotropic effects, which attained p ≤ 5 × 10−8 in the univariate GWAS. We showed that a large fraction of the pleiotropic associations was affected by a counterintuitive phenomenon of antagonistic genetic heterogeneity, which explains the increase, rather than decrease, of the significance of the pleiotropic associations in the omnibus test. Functional enrichment analysis showed that apart from cancers, gene set harboring the non-pleiotropic SNPs was characterized by late-onset AD and neurodevelopmental disorders. The pleiotropic gene set was characterized by a broad spectrum of progressive neurological and neuromuscular diseases and immune-mediated conditions, including progressive motor neuropathy, multiple sclerosis, Parkinson’s disease, and severe AD. Our results suggest that disentangling genes harboring variants with and without pleiotropic associations with AD and EDU is promising for dissecting heterogeneity in biological mechanisms of AD.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11357-021-00484-1.

Heterogeneous neuropsychiatric phenotypes in two adult patients with 22q11.2 deletion syndrome (DiGeorge's syndrome): acase for RDoC?

Das DiGeorge-Syndrom ist eines der häufigsten Mikrodeletionssyndrome und bedingt ein erhöhtes Risiko für neuropsychiatrische Störungen der Intelligenz, der sozialen Kommunikation und der Exekutivfunktionen sowie psychotische Störungen. Im Falle des vorgestellten männlichen Patienten handelt es sich um die seltene Beschreibung eines Tourette-Syndroms auf der Grundlage eines 22q11.2-Mikrodeletionssyndroms. Die folgenden zwei Fallbeispiele demonstrieren die Vielfalt assoziierter klinischer Präsentationen, selbst auf der Grundlage einer übereinstimmenden und umschriebenen genetischen Aberration. Eine Charakterisierung solcher Patient*innen im Kontext der klinisch-wissenschaftlichen Praxis anhand der Research Domain Criteria (RDoC) ermöglicht eine transdiagnostische Beschreibung der überlappenden wie auch spezifischen neuropsychiatrischen Funktionseinschränkungen. Eine solche dimensionale Charakterisierung erlaubt somit potenziell auch eine genauere Differenzierung pleiotroper Assoziationen zwischen Genotyp und Phänotyp.

Mendelian Randomization Analysis Identified Potential Genes Pleiotropically Associated with Polycystic Ovary Syndrome.

Polycystic ovary syndrome (PCOS) is a common endocrine disorder with unclear etiology. Some genes may be pleiotropically or potentially causally associated with PCOS. In the present study, the summary data-based Mendelian randomization (SMR) method integrating genome-wide association study (GWAS) for PCOS and expression quantitative trait loci (eQTL) data was applied to identify genes that were pleiotropically associated with PCOS. Separate SMR analysis was performed using eQTL data in the ovary and whole blood. Although no genes showed significant pleiotropic association with PCOS after correction for multiple testing, some of the genes exhibited suggestive significance. RPS26 showed the strongest suggestive pleiotropic association with PCOS in both SMR analyses (β[SE]=0.10[0.03], PSMR=1.72×10−4 for ovary; β[SE]=0.11[0.03], PSMR=1.40×10−4 for whole blood). PM20D1 showed the second strongest suggestive pleiotropic association with PCOS in the SMR analysis using eQTL data for the whole blood and was also among the top ten hit genes in the SMR analysis using eQTL data for the ovary. Two other genes, including CTC-457L16.2 and NEIL2, were among the top ten hit genes in both SMR analyses. In conclusion, this study revealed multiple genes that were potentially involved in the pathogenesis of PCOS.

Identification of novel genome-wide pleiotropic associations with oral inflammatory traits.

Oral inflammatory diseases (OIDs) are a group of dental diseases with multiple clinical manifestations that impact the majority of the world's population. Many studies have investigated the associations between individual OID traits and genomic variants, but whether pleiotropic loci are shared by oral inflammatory traits remains poorly understood. Here, we conducted multitrait joint analyses based on the summary statistics of genome-wide association studies (GWASs) of five dental traits from the UK Biobank. Among these genome-wide significant loci, two were novel for both painful gums and toothache. We identified causal variants at each novel locus, and functional annotation based on multiomics data suggested IL10 and IL12A/TRIM59 as potential candidate genes at the novel pleiotropic loci. Subsequent analyses of pathway enrichment and protein-protein interaction networks suggested the involvement of the candidate genes in immune regulation. In conclusion, our results uncover novel pleiotropic loci for OID traits and highlight the importance of immune regulation in the pathogenesis of OIDs. These findings will enhance our understanding of the pathogenesis of OIDs and be beneficial for risk screening, prevention, and the development of novel drugs targeting the immune regulation of OIDs.

Assessing the Causal Relationships Between Insulin Resistance and Hyperuricemia and Gout Using Bidirectional Mendelian Randomization.

Hyperuricemia is closely associated with insulin resistance syndrome (and its many cardiometabolic sequelae); however, whether they are causally related has long been debated. We undertook this study to investigate the potential causal nature and direction between insulin resistance and hyperuricemia, along with gout, by using bidirectional Mendelian randomization (MR) analyses. We used genome-wide association data (n = 288,649 for serum urate [SU] concentration; n = 763,813 for gout risk; n = 153,525 for fasting insulin) to select genetic instruments for 2-sample MR analyses, using multiple MR methods to address potential pleiotropic associations. We then used individual-level, electronic medical record-linked data from the UK Biobank (n = 360,453 persons of European ancestry) to replicate our analyses via single-sample MR analysis. Genetically determined SU levels, whether inferred from a polygenic score or strong individual loci, were not associated with fasting insulin concentrations. In contrast, genetically determined fasting insulin concentrations were positively associated with SU levels (0.37 mg/dl per log-unit increase in fasting insulin [95% confidence interval (95% CI) 0.15, 0.58]; P = 0.001). This persisted in outlier-corrected (β = 0.56 mg/dl [95% CI 0.45, 0.67]) and multivariable MR analyses adjusted for BMI (β = 0.69 mg/dl [95% CI 0.53, 0.85]) (P < 0.001 for both). Polygenic scores for fasting insulin were also positively associated with SU level among individuals in the UK Biobank (P < 0.001). Findings for gout risk were bidirectionally consistent with those for SU level. These findings provide evidence to clarify core questions about the close association between hyperuricemia and insulin resistance syndrome: hyperinsulinemia leads to hyperuricemia but not the other way around. Reducing insulin resistance could lower the SU level and gout risk, whereas lowering the SU level (e.g., allopurinol treatment) is unlikely to mitigate insulin resistance and its cardiometabolic sequelae.

Identifying pleiotropic genes for complex phenotypes with summary statistics from a perspective of composite null hypothesis testing.

Pleiotropy has important implication on genetic connection among complex phenotypes and facilitates our understanding of disease etiology. Genome-wide association studies provide an unprecedented opportunity to detect pleiotropic associations; however, efficient pleiotropy test methods are still lacking. We here consider pleiotropy identification from a methodological perspective of high-dimensional composite null hypothesis and propose a powerful gene-based method called MAIUP. MAIUP is constructed based on the traditional intersection-union test with two sets of independent P-values as input and follows a novel idea that was originally proposed under the high-dimensional mediation analysis framework. The key improvement of MAIUP is that it takes the composite null nature of pleiotropy test into account by fitting a three-component mixture null distribution, which can ultimately generate well-calibrated P-values for effective control of family-wise error rate and false discover rate. Another attractive advantage of MAIUP is its ability to effectively address the issue of overlapping subjects commonly encountered in association studies. Simulation studies demonstrate that compared with other methods, only MAIUP can maintain correct type I error control and has higher power across a wide range of scenarios. We apply MAIUP to detect shared associated genes among 14 psychiatric disorders with summary statistics and discover many new pleiotropic genes that are otherwise not identified if failing to account for the issue of composite null hypothesis testing. Functional and enrichment analyses offer additional evidence supporting the validity of these identified pleiotropic genes associated with psychiatric disorders. Overall, MAIUP represents an efficient method for pleiotropy identification.

Novel DNA methylation loci and genes showing pleiotropic association with Alzheimer’s dementia: a network Mendelian randomization analysis

ABSTRACT Previous genome-wide association studies (GWAS) have identified potential genetic variants involved in the risk of Alzheimer’s dementia, but their underlying biological interpretation remains largely unclear. In addition, the effects of DNA methylation and gene expression on Alzheimer’s dementia are not well understood. A network summary data-based Mendelian randomization (SMR) analysis was performed integrating cis- DNA methylation quantitative trait loci (mQTL) /cis- gene expression QTL (eQTL) data in the brain and blood, as well as GWAS summarized data for Alzheimer’s dementia to evaluate the pleiotropic associations of DNA methylation and gene expression with Alzheimer’s dementia and to explore the complex mechanisms underpinning Alzheimer’s dementia. After correction for multiple testing (false discovery rate [FDR] P < 0.05) and filtering using the heterogeneity in dependent instruments (HEIDI) test (P HEIDI>0.01), we identified dozens of DNA methylation sites and genes showing pleiotropic associations with Alzheimer’s dementia. We found 22 and 16 potentially causal pathways of Alzheimer’s dementia (i.e., SNP→DNA methylation→Gene expression→Alzheimer’s dementia) in the brain and blood, respectively. Approximately two-thirds of the identified DNA methylation sites had an influence on gene expression and the expression of almost all the identified genes was regulated by DNA methylation. Our network SMR analysis provided evidence supporting the pleiotropic association of some novel DNA methylation sites and genes with Alzheimer’s dementia and revealed possible causal pathways underlying the pathogenesis of Alzheimer’s dementia. Our findings shed light on the role of DNA methylation in gene expression and in the development of Alzheimer’s dementia.

Genomic and pleiotropic analyses of resting QT interval identifies novel loci and overlap with atrial electrical disorders.

The resting QT interval, an electrocardiographic (ECG) measure of ventricular myocardial repolarization, is a heritable risk marker of cardiovascular mortality, but the mechanisms remain incompletely understood. Previously reported candidate genes have provided insights into the regulatory mechanisms of the QT interval. However, there are still important knowledge gaps. We aimed to gain new insights by (i) providing new candidate genes, (ii) identifying pleiotropic associations with other cardiovascular traits, and (iii) scanning for sexually dimorphic genetic effects. We conducted a genome-wide association analysis for resting QT interval with ~9.8 million variants in 52 107 individuals of European ancestry without known cardiovascular disease from the UK Biobank. We identified 40 loci, 13 of which were novel, including 2 potential sex-specific loci, explaining ~11% of the trait variance. Candidate genes at novel loci were involved in myocardial structure and arrhythmogenic cardiomyopathy. Investigation of pleiotropic effects of QT interval variants using phenome-wide association analyses in 302 000 unrelated individuals from the UK Biobank and pairwise genome-wide comparisons with other ECG and cardiac imaging traits revealed genetic overlap with atrial electrical pathology. These findings provide novel insights into how abnormal myocardial repolarization and increased cardiovascular mortality may be linked.

Mendelian randomization analysis identified genes pleiotropically associated with central corneal thickness

ObjectiveTo prioritize genes that were pleiotropically or potentially causally associated with central corneal thickness (CCT).MethodsWe applied the summary data-based Mendelian randomization (SMR) method integrating summarized data of genome-wide association study (GWAS) on CCT and expression quantitative trait loci (eQTL) data to identify genes that were pleiotropically associated with CCT. We performed separate SMR analysis using CAGE eQTL data and GTEx eQTL data. SMR analyses were done for participants of European and East Asian ancestries, separately.ResultsWe identified multiple genes showing pleiotropic association with CCT in the participants of European ancestry. CLIC3 (ILMN_1796423; PSMR = 4.15 × 10− 12), PTGDS (ILMN_1664464; PSMR = 6.88 × 10− 9) and C9orf142 (ILMN_1761138; PSMR = 8.09 × 10− 9) were the top three genes using the CAGE eQTL data, and RP11-458F8.4 (ENSG00000273142.1; PSMR = 5.89 × 10− 9), LCNL1 (ENSG00000214402.6; PSMR = 5.67 × 10− 8), and PTGDS (ENSG00000107317.7; PSMR = 1.92 × 10− 7) were the top three genes using the GTEx eQTL data. No genes showed significantly pleiotropic association with CCT in the participants of East Asian ancestry after correction for multiple testing.ConclusionWe identified several genes pleiotropically associated with CCT, some of which represented novel genes influencing CCT. Our findings provided important leads to a better understanding of the genetic factors influencing CCT, and revealed potential therapeutic targets for the treatment of primary open-angle glaucoma and keratoconus.

Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder.

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders. We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific. We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001). Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

Genome-wide association study suggests an independent genetic basis of zinc and cadmium concentrations in fresh sweet corn kernels.

Despite being one of the most consumed vegetables in the United States, the elemental profile of sweet corn (Zea mays L.) is limited in its dietary contributions. To address this through genetic improvement, a genome-wide association study was conducted for the concentrations of 15 elements in fresh kernels of a sweet corn association panel. In concordance with mapping results from mature maize kernels, we detected a probable pleiotropic association of zinc and iron concentrations with nicotianamine synthase5 (nas5), which purportedly encodes an enzyme involved in synthesis of the metal chelator nicotianamine. In addition, a pervasive association signal was identified for cadmium concentration within a recombination suppressed region on chromosome 2. The likely causal gene underlying this signal was heavy metal ATPase3 (hma3), whose counterpart in rice, OsHMA3, mediates vacuolar sequestration of cadmium and zinc in roots, whereby regulating zinc homeostasis and cadmium accumulation in grains. In our association panel, hma3 associated with cadmium but not zinc accumulation in fresh kernels. This finding implies that selection for low cadmium will not affect zinc levels in fresh kernels. Although less resolved association signals were detected for boron, nickel, and calcium, all 15 elements were shown to have moderate predictive abilities via whole-genome prediction. Collectively, these results help enhance our genomics-assisted breeding efforts centered on improving the elemental profile of fresh sweet corn kernels.

Heritable genetic variants in key cancer genes link cancer risk with anthropometric traits

BackgroundHeight and other anthropometric measures are consistently found to associate with differential cancer risk. However, both genetic and mechanistic insights into these epidemiological associations are notably lacking. Conversely, inherited genetic...

Utilising multi-large omics data to elucidate biological mechanisms within multiple sclerosis genetic susceptibility loci

Background: Genome-wide association studies (GWAS) have succeeded in identifying over 200 susceptibility loci for multiple sclerosis (MS). However, the potential functional variants and the mechanisms by which these loci affect MS risk remain largely unexplained. Objectives: We used summary data-based Mendelian randomisation to prioritise risk genes and infer potential biological mechanisms for MS risk loci. Methods: The data used consisted of DNA methylation (n = 1980) QTL (mQTL) and gene expression (n = 31,684) QTL (eQTL) derived from whole blood as well as MS GWAS summary statistics (14,802 cases, 26,703 controls). The findings were further evaluated using data derived from independent brain mQTL (n = 1160) and eQTL (n = 1194). Results: In whole blood, we identified two independent genomic loci (lincRNA: RP11-326C3.13 and TNFSF14) with consistent genome-wide significant pleiotropic associations across different omics layers. In brain tissue, a similar effect for the RP11-326C3.13 locus was observed but not for TNFSF14, indicating a potential tissue-specific effect for the TNFSF14 locus. Conclusion: We provide in silico evidence for the putative biological mechanisms by which the identified DNA methylation sites and target genes are functionally relevant to MS development in different tissues. Future research targeting these genes and DNA methylation sites will determine their roles in the pathophysiology of MS.

Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder

Previous genome-wide association studies (GWAS) have identified potential genetic variants associated with the risk of major depressive disorder (MDD), but the underlying biological interpretation remains largely unknown. We aimed to prioritize genes that were pleiotropically or potentially causally associated with MDD. We applied the summary data-based Mendelian randomization (SMR) method integrating GWAS and gene expression quantitative trait loci (eQTL) data in 13 brain regions to identify genes that were pleiotropically associated with MDD. In addition, we repeated the analysis by using the meta-analyzed version of the eQTL summary data in the brain (brain-eMeta). We identified multiple significant genes across different brain regions that may be involved in the pathogenesis of MDD. The prime-specific gene BTN3A2 (corresponding probe: ENSG00000186470.9) was the top hit showing pleiotropic association with MDD in 9 of the 13 brain regions and in brain-eMeta, after correction for multiple testing. Many of the identified genes are located in the human major histocompatibility complex (MHC) region on chromosome 6 and are mainly involved in the immune response. Our SMR analysis indicated that multiple genes showed pleiotropic association with MDD across the brain regions. These findings provided important leads to a better understanding of the mechanism of MDD and revealed potential therapeutic targets for the prevention and effective treatment of MDD.

Mendelian randomization analysis identified genes potentially pleiotropically associated with periodontitis.

ObjectiveTo prioritize genes that were pleiotropically or potentially causally associated with periodontitis.MethodsWe applied the summary data-based Mendelian randomization (SMR) method integrating genome-wide association study (GWAS) for periodontitis and expression quantitative trait loci (eQTL) data to identify genes that were pleiotropically associated with periodontitis. We performed separate SMR analysis using CAGE eQTL data and GTEx eQTL data. SMR analysis were done for participants of European and East Asian ancestries, separately.ResultsWe identified multiple genes showing pleiotropic association with periodontitis in participants of European ancestry and participants of East Asian ancestry. PDCD2 (corresponding probe: ILMN_1758915) was the top hit showing pleotropic association with periodontitis in the participants of European ancestry using CAGE eQTL data, and BX093763 (corresponding probe: ILMN_1899903) and AC104135.3 (corresponding probe: ENSG00000204792.2) were the top hits in the participants of East Asian ancestry using CAGE eQTL data and GTEx eQTL data, respectively.ConclusionWe identified multiple genes that may be involved in the pathogenesis of periodontitis in participants of European ancestry and participants of East Asian ancestry. Our findings provided important leads to a better understanding of the mechanisms underlying periodontitis and revealed potential therapeutic targets for the effective treatment of periodontitis.

Insomnia and Coronary Artery Diseases: A Mendelian Randomisation Study

Abstract Objective: Observational studies indicate that insomnia may increase the risk of developing and/or dying from cardiovascular diseases, especially coronary artery disease (CAD). Our purpose is to explore the underlying causal relationship between genetic variants susceptible to insomnia and the risk of CAD by Mendelian randomization analysis. Methods: The study was conducted using publicly available statistical data on genetic variants identified from a genome-wide association meta-analysis of insomnia (n = 113,006 individuals) and a genome-wide association meta-analysis of CAD (n = 184,305 individuals), which consisted of both cases and non-cases. The genetic association between variants and CAD was assessed by the variants’ association with insomnia, and estimations were integrated by an inverse-variance weighted meta-analysis. Results: Among the Mendelian randomized analytical sample, 8 variants were associated with insomnia complaints and CAD. And there was no pleiotropic association with the latent confounders. In addition, in the inverse-variance weighted meta-analysis (the estimations combined from the 8 variants), the odds ratio was 1.15 (95% CI: 1.05–1.25; P = 0.002) for CAD, and in the weighted method analysis, the odds ratio was 1.14 (95% CI: 1.03–1.27; P = 0.015) for CAD. Conclusions: All of the data indicated that some valuable variants might involve in the development of CAD by leading the insomnia. Therefore, insomnia might be a causal factor for CAD, and improving the quality of sleep might be a new way for populations with insomnia to prevent CAD.

Pleiotropic associations of heterozygosity for the SERPINA1 Z allele in the UK Biobank.

Homozygosity for the SERPINA1 Z allele causes α1-antitrypsin deficiency, a rare condition that can cause lung and liver disease. However, the effects of Z allele heterozygosity on nonrespiratory phenotypes, and on lung function in the general population, remain unclear.We conducted a large, population-based study to determine Z allele effects on >2400 phenotypes in the UK Biobank (N=303 353).Z allele heterozygosity was strongly associated with increased height (β=1.02 cm, p=3.91×10−68), and with other nonrespiratory phenotypes including increased risk of gall bladder disease, reduced risk of heart disease and lower blood pressure, reduced risk of osteoarthritis and reduced bone mineral density, increased risk of headache and enlarged prostate, as well as with blood biomarkers of liver function. Heterozygosity was associated with higher height-adjusted forced expiratory volume in 1 s (FEV1) (β=19.36 mL, p=9.21×10−4) and FEV1/forced vital capacity (β=0.0031, p=1.22×10−5) in nonsmokers, whereas in smokers, this protective effect was abolished. Furthermore, we show for the first time that sex modifies the association of the Z allele on lung function.We conclude that Z allele heterozygosity and homozygosity exhibit opposing effects on lung function in the UK population, and that these associations are modified by smoking and sex. In exploratory analyses, heterozygosity for the Z allele also showed pleiotropic associations with nonrespiratory health-related traits and disease risk.