Publications by authors named "Grant W Montgomery"

535 Publications

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 Jun 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Genetic Regulation of Physiological Reproductive Lifespan and Female Fertility.

Int J Mol Sci 2021 Mar 4;22(5). Epub 2021 Mar 4.

Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, St Lucia, QLD 4072, Australia.

There is substantial genetic variation for common traits associated with reproductive lifespan and for common diseases influencing female fertility. Progress in high-throughput sequencing and genome-wide association studies (GWAS) have transformed our understanding of common genetic risk factors for complex traits and diseases influencing reproductive lifespan and fertility. The data emerging from GWAS demonstrate the utility of genetics to explain epidemiological observations, revealing shared biological pathways linking puberty timing, fertility, reproductive ageing and health outcomes. The observations also identify unique genetic risk factors specific to different reproductive diseases impacting on female fertility. Sequencing in patients with primary ovarian insufficiency (POI) have identified mutations in a large number of genes while GWAS have revealed shared genetic risk factors for POI and ovarian ageing. Studies on age at menopause implicate DNA damage/repair genes with implications for follicle health and ageing. In addition to the discovery of individual genes and pathways, the increasingly powerful studies on common genetic risk factors help interpret the underlying relationships and direction of causation in the regulation of reproductive lifespan, fertility and related traits.
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http://dx.doi.org/10.3390/ijms22052556DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7961500PMC
March 2021

Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders.

Genome Biol 2021 Mar 26;22(1):90. Epub 2021 Mar 26.

Centre for Clinical Research, The University of Queensland, Brisbane, QLD, 4019, Australia.

Background: People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease.

Results: We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson's disease (and none with Alzheimer's disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights.

Conclusions: We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.
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http://dx.doi.org/10.1186/s13059-021-02275-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004462PMC
March 2021

Comparison of Familial, Polygenic and Biochemical Predictors of Mortality.

Twin Res Hum Genet 2020 12 29;23(6):307-315. Epub 2021 Jan 29.

Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.

Mortality risk is known to be associated with many physiological or biochemical risk factors, and polygenic risk scores (PRSs) may offer an additional or alternative approach to risk stratification. We have compared the predictive value of common biochemical tests, PRSs and information on parental survival in a cohort of twins and their families. Common biochemical test results were available for up to 13,365 apparently healthy men and women, aged 17-93 years (mean 49.0, standard deviation [SD] 13.7) at blood collection. PRSs for longevity were available for 14,169 study participants and reported parental survival for 25,784 participants. A search for information on date and cause of death was conducted through the Australian National Death Index, with median follow-up of 11.3 years. Cox regression was used to evaluate associations with mortality from all causes, cancers, cardiovascular diseases and other causes. Linear relationships with all-cause mortality were strongest for C-reactive protein, gamma-glutamyl transferase, glucose and alkaline phosphatase, with hazard ratios (HRs) of 1.16 (95% CI [1.07, 1.24]), 1.15 (95% CI 1.04-1.21), 1.13 (95% CI [1.08, 1.19]) and 1.11 (95% CI [1.05, 1.88]) per SD difference, respectively. Significant nonlinear effects were found for urea, uric acid and butyrylcholinesterase. Lipid risk factors were not statistically significant for mortality in our cohort. Family history and PRS showed weaker but significant associations with survival, with HR in the range 1.05 to 1.09 per SD difference. In conclusion, biochemical tests currently predict long-term mortality more strongly than genetic scores based on genotyping or on reported parental survival.
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http://dx.doi.org/10.1017/thg.2020.89DOI Listing
December 2020

Germline variants are associated with increased primary melanoma tumor thickness at diagnosis.

Hum Mol Genet 2021 01;29(21):3578-3587

Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, 4006, Australia.

Germline genetic variants have been identified, which predispose individuals and families to develop melanoma. Tumor thickness is the strongest predictor of outcome for clinically localized primary melanoma patients. We sought to determine whether there is a heritable genetic contribution to variation in tumor thickness. If confirmed, this will justify the search for specific genetic variants influencing tumor thickness. To address this, we estimated the proportion of variation in tumor thickness attributable to genome-wide genetic variation (variant-based heritability) using unrelated patients with measured primary cutaneous melanoma thickness. As a secondary analysis, we conducted a genome-wide association study (GWAS) of tumor thickness. The analyses utilized 10 604 individuals with primary cutaneous melanoma drawn from nine GWAS datasets from eight cohorts recruited from the general population, primary care and melanoma treatment centers. Following quality control and filtering to unrelated individuals with study phenotypes, 8125 patients were used in the primary analysis to test whether tumor thickness is heritable. An expanded set of 8505 individuals (47.6% female) were analyzed for the secondary GWAS meta-analysis. Analyses were adjusted for participant age, sex, cohort and ancestry. We found that 26.6% (SE 11.9%, P = 0.0128) of variation in tumor thickness is attributable to genome-wide genetic variation. While requiring replication, a chromosome 11 locus was associated (P < 5 × 10-8) with tumor thickness. Our work indicates that sufficiently large datasets will enable the discovery of genetic variants associated with greater tumor thickness, and this will lead to the identification of host biological processes influencing melanoma growth and invasion.
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http://dx.doi.org/10.1093/hmg/ddaa222DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788289PMC
January 2021

The genetic architecture of sporadic and multiple consecutive miscarriage.

Nat Commun 2020 11 25;11(1):5980. Epub 2020 Nov 25.

University of Queensland, St Lucia, QLD, Australia.

Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10, odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10, OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10, OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10, OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.
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http://dx.doi.org/10.1038/s41467-020-19742-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7689465PMC
November 2020

Commentary: lessons from molecular genetic studies on reporting false-positive results.

Reprod Fertil Dev 2020 Nov;32(16):1298-1300

Institute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, St Lucia, Qld 4072, Australia. Email:

Poor replication of published research results is the subject of debate. A common problem is the failure to adequately account for multiple testing issues. In this regard, the evolution of mapping studies to identify genetic risk factors for common diseases has been instructive. Large genome-wide association studies (GWAS) reliably detect the genetic factors with small effects that contribute to risk for many common diseases. GWAS superseded candidate gene studies from the previous decade and looking back, almost no genetic risk factors reported from earlier candidate gene studies replicate in the GWAS results. Candidate gene studies often used small samples and failed to appreciate and adequately account for the multiple testing issues. The failure to replicate results from most candidate gene studies highlights the importance of study power and appropriate statistical analysis to prevent publication of false-positive results.
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http://dx.doi.org/10.1071/RD20281DOI Listing
November 2020

Comparison of Genome-Wide Association Scans for Quantitative and Observational Measures of Human Hair Curvature.

Twin Res Hum Genet 2020 10;23(5):271-277

Psychiatric Genetics, Genetics and Computational Biology Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia.

Previous genetic studies on hair morphology focused on the overall morphology of the hair using data collected by self-report or researcher observation. Here, we present the first genome-wide association study (GWAS) of a micro-level quantitative measure of hair curvature. We compare these results to GWAS results obtained using a macro-level classification of observable hair curvature performed in the same sample of twins and siblings of European descent. Observational data were collected by trained observers, while quantitative data were acquired using an Optical Fibre Diameter Analyser (OFDA). The GWAS for both the observational and quantitative measures of hair curvature resulted in genome-wide significant signals at chromosome 1q21.3 close to the trichohyalin (TCHH) gene, previously shown to harbor variants associated with straight hair morphology in Europeans. All genetic variants reaching genome-wide significance for both GWAS (quantitative measure lead single-nucleotide polymorphism [SNP] rs12130862, p = 9.5 × 10-09; observational measure lead SNP rs11803731, p = 2.1 × 10-17) were in moderate to very high linkage disequilibrium (LD) with each other (minimum r2 = .45), indicating they represent the same genetic locus. Conditional analyses confirmed the presence of only one signal associated with each measure at this locus. Results from the quantitative measures reconfirmed the accuracy of observational measures.
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http://dx.doi.org/10.1017/thg.2020.78DOI Listing
October 2020

Cellular Origins of Endometriosis: Towards Novel Diagnostics and Therapeutics.

Semin Reprod Med 2020 05 11;38(2-03):201-215. Epub 2020 Nov 11.

The Ritchie Centre, Hudson Institute of Medical Research, Department of Obstetrics and Gynaecology, Monash University, Melbourne, Victoria, Australia.

Endometriosis remains an enigmatic disease of unknown etiology, with delayed diagnosis and poor therapeutic options. This review will discuss the cellular, physiological, and genomic evidence of Sampson's hypothesis of retrograde menstruation as a cause of pelvic endometriosis and as the basis of phenotypic heterogeneity of the disease. We postulate that collaborative research at the single cell level focused on unlocking the cellular, physiological, and genomic mechanisms of endometriosis will be accompanied by advances in personalized diagnosis and therapies that target unique subtypes of endometriosis disease. These advances will address the clinical conundrums of endometriosis clinical care-including diagnostic delay, suboptimal treatments, disease recurrence, infertility, chronic pelvic pain, and quality of life. There is an urgent need to improve outcomes for women with endometriosis. To achieve this, it is imperative that we understand which cells form the lesions, how they arrive at distant sites, and what factors govern their ability to survive and invade at ectopic locations. This review proposes new research avenues to address these basic questions of endometriosis pathobiology that will lay the foundations for new diagnostic tools and treatment pathways.
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http://dx.doi.org/10.1055/s-0040-1713429DOI Listing
May 2020

A large-scale genome-wide association study meta-analysis of cannabis use disorder.

Lancet Psychiatry 2020 12 20;7(12):1032-1045. Epub 2020 Oct 20.

Stanford University Graduate School of Education, Stanford University, Stanford, CA, USA.

Background: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.

Methods: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations.

Findings: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10). Cannabis use disorder and cannabis use were genetically correlated (r 0·50, p=1·50 × 10), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia.

Interpretation: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.

Funding: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.
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http://dx.doi.org/10.1016/S2215-0366(20)30339-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7674631PMC
December 2020

Genetic analysis of endometriosis and depression identifies shared loci and implicates causal links with gastric mucosa abnormality.

Hum Genet 2021 Mar 21;140(3):529-552. Epub 2020 Sep 21.

School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, QLD, Australia.

Evidence from observational studies indicates that endometriosis and depression often co-occur. However, conflicting evidence exists, and the etiology as well as biological mechanisms underlying their comorbidity remain unknown. Utilizing genome-wide association study (GWAS) data, we comprehensively assessed the relationship between endometriosis and depression. Single nucleotide polymorphism effect concordance analysis (SECA) found a significant genetic overlap between endometriosis and depression (P = 9.99 × 10). Linkage disequilibrium score regression (LDSC) analysis estimated a positive and highly significant genetic correlation between the two traits (r = 0.27, P = 8.85 × 10). A meta-analysis of endometriosis and depression GWAS (sample size = 709,111), identified 20 independent genome-wide significant loci (P < 5 × 10), of which eight are novel. Mendelian randomization analysis (MR) suggests a causal effect of depression on endometriosis. Combining gene-based association results across endometriosis and depression GWAS, we identified 22 genes with a genome-wide significant Fisher's combined P value (FCP < 2.75 × 10). Genes with a nominal gene-based association (P < 0.05) were significantly enriched across endometriosis and depression (P = 2.90 × 10). Also, genes overlapping the two traits at P < 0.1 (P = 1.31 × 10) were significantly enriched for the biological pathways 'cell-cell adhesion', 'inositol phosphate metabolism', 'Hippo-Merlin signaling dysregulation' and 'gastric mucosa abnormality'. These results reveal a shared genetic etiology for endometriosis and depression. Indeed, additional analyses found evidence of a causal association between each of endometriosis and depression and at least one abnormal condition of gastric mucosa. Our study confirms the comorbidity of endometriosis and depression, implicates links with gastric mucosa abnormalities in their causal pathways and reveals potential therapeutic targets for further investigation.
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http://dx.doi.org/10.1007/s00439-020-02223-6DOI Listing
March 2021

Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts.

Sci Rep 2020 07 29;10(1):12681. Epub 2020 Jul 29.

Washington State Twin Registry, Washington State University - Health Sciences Spokane, Spokane, WA, USA.

We investigated the heritability of educational attainment and how it differed between birth cohorts and cultural-geographic regions. A classical twin design was applied to pooled data from 28 cohorts representing 16 countries and including 193,518 twins with information on educational attainment at 25 years of age or older. Genetic factors explained the major part of individual differences in educational attainment (heritability: a = 0.43; 0.41-0.44), but also environmental variation shared by co-twins was substantial (c = 0.31; 0.30-0.33). The proportions of educational variation explained by genetic and shared environmental factors did not differ between Europe, North America and Australia, and East Asia. When restricted to twins 30 years or older to confirm finalized education, the heritability was higher in the older cohorts born in 1900-1949 (a = 0.44; 0.41-0.46) than in the later cohorts born in 1950-1989 (a = 0.38; 0.36-0.40), with a corresponding lower influence of common environmental factors (c = 0.31; 0.29-0.33 and c = 0.34; 0.32-0.36, respectively). In conclusion, both genetic and environmental factors shared by co-twins have an important influence on individual differences in educational attainment. The effect of genetic factors on educational attainment has decreased from the cohorts born before to those born after the 1950s.
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http://dx.doi.org/10.1038/s41598-020-69526-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391756PMC
July 2020

Multiplex melanoma families are enriched for polygenic risk.

Hum Mol Genet 2020 10;29(17):2976-2985

Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia.

Cancers, including cutaneous melanoma, can cluster in families. In addition to environmental etiological factors such as ultraviolet radiation, cutaneous melanoma has a strong genetic component. Genetic risks for cutaneous melanoma range from rare, high-penetrance mutations to common, low-penetrance variants. Known high-penetrance mutations account for only about half of all densely affected cutaneous melanoma families, and the causes of familial clustering in the remainder are unknown. We hypothesize that some clustering is due to the cumulative effect of a large number of variants of individually small effect. Common, low-penetrance genetic risk variants can be combined into polygenic risk scores. We used a polygenic risk score for cutaneous melanoma to compare families without known high-penetrance mutations with unrelated melanoma cases and melanoma-free controls. Family members had significantly higher mean polygenic load for cutaneous melanoma than unrelated cases or melanoma-free healthy controls (Bonferroni-corrected t-test P = 1.5 × 10-5 and 6.3 × 10-45, respectively). Whole genome sequencing of germline DNA from 51 members of 21 families with low polygenic risk for melanoma identified a CDKN2A p.G101W mutation in a single family but no other candidate high-penetrance melanoma susceptibility genes. This work provides further evidence that melanoma, like many other common complex disorders, can arise from the joint action of multiple predisposing factors, including rare high-penetrance mutations, as well as via a combination of large numbers of alleles of small effect.
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http://dx.doi.org/10.1093/hmg/ddaa156DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7566496PMC
October 2020

Obesity does not alter endometrial gene expression in women with endometriosis.

Reprod Biomed Online 2020 Jul 3;41(1):113-118. Epub 2020 May 3.

Department of Obstetrics and Gynhaecology, University of Melbourne and Gynaecology Research Centre, Level 7, Cnr Grattan St and Flemington Rd, Royal Women's Hospital, Parkville, Victoria 3052, Australia; Department of Anatomy, University of Otago, 270 Great King Street, Dunedin 9016, New Zealand.

Research Question: Does obesity affect endometrial gene expression in women with endometriosis, specifically women with stage I disease?

Design: Differential gene expression analysis was conducted on endometrium from women with and without endometriosis (n = 169). Women were diagnosed after surgical visualization and staged according to the revised American Society for Reproductive Medicine (stage I-IV). Women were grouped by body mass index (BMI) (kg/m) as underweight, normal, pre-obese or obese. After accounting for menstrual cycle stage, endometrial gene expression was analysed by BMI (continuous and grouped) in women with endometriosis, and in non-endometriosis controls.

Results: No significant interaction effect was found between BMI and endometriosis status on endometrial gene expression. We have previously reported that obese women with endometriosis have a reduced incidence of stage I disease; however, stratifying our analysis into stage I endometriosis versus combined II, III and IV endometriosis failed to reveal any differentially expressed endometrial genes between normal, pre-obese and obese patients.

Conclusions: Despite obesity having deleterious effects on endometrial gene expression in other gynaecological pathologies, e.g. endometrial cancer and polycystic ovary syndrome, our results do not support an association between BMI and altered endometrial gene expression in women with or without endometriosis.
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http://dx.doi.org/10.1016/j.rbmo.2020.03.015DOI Listing
July 2020

The Genetics of Endometriosis.

Twin Res Hum Genet 2020 04 19;23(2):103-104. Epub 2020 May 19.

Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.

Mapping genetic risk factors for endometriosis continues from early studies on women's health initiated by Nick Martin and Susan Treloar. Their initial recruitment of endometriosis cases and family members received a major boost and became a flagship project within the Cooperative Research Centre (CRC) for the Discovery of Common Human Disease. We extended the study through a formal collaboration with Professor Stephen Kennedy and his group in Oxford. Our first joint scientific meeting was held in Brisbane and was sadly memorable as the day the planes were flown into the Twin Towers in New York. Our initial collaboration expanded into the International Endometriosis Genetics Consortium (IEGC). The IEGC now has 15 groups around the world, and the most recent meta-analysis will be published this year.
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http://dx.doi.org/10.1017/thg.2020.36DOI Listing
April 2020

Genome-wide association meta-analyses combining multiple risk phenotypes provide insights into the genetic architecture of cutaneous melanoma susceptibility.

Nat Genet 2020 05 27;52(5):494-504. Epub 2020 Apr 27.

Department of Dermatology, Instituto Valenciano de Oncología, Valencia, Spain.

Most genetic susceptibility to cutaneous melanoma remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 cases of melanoma (67% newly genotyped) and 375,188 controls identified 54 significant (P < 5 × 10) loci with 68 independent single nucleotide polymorphisms. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with GWAS of nevus count and hair color, and transcriptome association approaches, uncovered 31 potential secondary loci for a total of 85 cutaneous melanoma susceptibility loci. These findings provide insights into cutaneous melanoma genetic architecture, reinforcing the importance of nevogenesis, pigmentation and telomere maintenance, together with identifying potential new pathways for cutaneous melanoma pathogenesis.
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http://dx.doi.org/10.1038/s41588-020-0611-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7255059PMC
May 2020

Authors' Reply.

J Minim Invasive Gynecol 2020 Sep - Oct;27(6):1427. Epub 2020 Apr 24.

San Francisco, California.

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http://dx.doi.org/10.1016/j.jmig.2020.04.021DOI Listing
December 2020

Shared Molecular Genetic Mechanisms Underlie Endometriosis and Migraine Comorbidity.

Genes (Basel) 2020 02 29;11(3). Epub 2020 Feb 29.

School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia.

Observational epidemiological studies indicate that endometriosis and migraine co-occur within individuals more than expected by chance. However, the aetiology and biological mechanisms underlying their comorbidity remain unknown. Here we examined the relationship between endometriosis and migraine using genome-wide association study (GWAS) data. Single nucleotide polymorphism (SNP) effect concordance analysis found a significant concordance of SNP risk effects across endometriosis and migraine GWAS. Linkage disequilibrium score regression analysis found a positive and highly significant genetic correlation ( = 0.38, = 2.30 × 10) between endometriosis and migraine. A meta-analysis of endometriosis and migraine GWAS data did not reveal novel genome-wide significant SNPs, and Mendelian randomisation analysis found no evidence for a causal relationship between the two traits. However, gene-based analyses identified two novel loci for migraine. Also, we found significant enrichment of genes nominally associated ( < 0.05) with both traits ( = 9.83 × 10). Combining gene-based p-values across endometriosis and migraine, three genes, two ( of which are at novel loci, were genome-wide significant. Genes having < 0.1 for both endometriosis and migraine ( = 1.85 ×10°) were significantly enriched for biological pathways, including interleukin-1 receptor binding, focal adhesion-PI3K-Akt-mTOR-signaling, MAPK and TNF-α signalling. Our findings further confirm the comorbidity of endometriosis and migraine and indicate a non-causal relationship between the two traits, with shared genetically-controlled biological mechanisms underlying the co-occurrence of the two disorders.
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http://dx.doi.org/10.3390/genes11030268DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140889PMC
February 2020

Genome-wide Association Analysis in Humans Links Nucleotide Metabolism to Leukocyte Telomere Length.

Am J Hum Genet 2020 03 27;106(3):389-404. Epub 2020 Feb 27.

Department of Cardiovascular Sciences, University of Leicester, LE3 9QP, United Kingdom; NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, LE3 9QP, United Kingdom.

Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.
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http://dx.doi.org/10.1016/j.ajhg.2020.02.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058826PMC
March 2020

Tissue specific regulation of transcription in endometrium and association with disease.

Hum Reprod 2020 02;35(2):377-393

The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.

Study Question: Are genetic effects on endometrial gene expression tissue specific and/or associated with reproductive traits and diseases?

Summary Answer: Analyses of RNA-sequence data and individual genotype data from the endometrium identified novel and disease associated, genetic mechanisms regulating gene expression in the endometrium and showed evidence that these mechanisms are shared across biologically similar tissues.

What Is Known Already: The endometrium is a complex tissue vital for female reproduction and is a hypothesized source of cells initiating endometriosis. Understanding genetic regulation specific to, and shared between, tissue types can aid the identification of genes involved in complex genetic diseases.

Study Design, Size, Duration: RNA-sequence and genotype data from 206 individuals was analysed and results were compared with large publicly available datasets.

Participants/materials, Setting, Methods: RNA-sequencing and genotype data from 206 endometrial samples was used to identify the influence of genetic variants on gene expression, via expression quantitative trait loci (eQTL) analysis and to compare these endometrial eQTLs with those in other tissues. To investigate the association between endometrial gene expression regulation and reproductive traits and diseases, we conducted a tissue enrichment analysis, transcriptome-wide association study (TWAS) and summary data-based Mendelian randomisation (SMR) analyses. Transcriptomic data was used to test differential gene expression between women with and without endometriosis.

Main Results And The Role Of Chance: A tissue enrichment analysis with endometriosis genome-wide association study summary statistics showed that genes surrounding endometriosis risk loci were significantly enriched in reproductive tissues. A total of 444 sentinel cis-eQTLs (P < 2.57 × 10-9) and 30 trans-eQTLs (P < 4.65 × 10-13) were detected, including 327 novel cis-eQTLs in endometrium. A large proportion (85%) of endometrial eQTLs are present in other tissues. Genetic effects on endometrial gene expression were highly correlated with the genetic effects on reproductive (e.g. uterus, ovary) and digestive tissues (e.g. salivary gland, stomach), supporting a shared genetic regulation of gene expression in biologically similar tissues. The TWAS analysis indicated that gene expression at 39 loci is associated with endometriosis, including five known endometriosis risk loci. SMR analyses identified potential target genes pleiotropically or causally associated with reproductive traits and diseases including endometriosis. However, without taking account of genetic variants, a direct comparison between women with and without endometriosis showed no significant difference in endometrial gene expression.

Large Scale Data: The eQTL dataset generated in this study is available at http://reproductivegenomics.com.au/shiny/endo_eqtl_rna/. Additional datasets supporting the conclusions of this article are included within the article and the supplementary information files, or are available on reasonable request.

Limitations, Reasons For Caution: Data are derived from fresh tissue samples and expression levels are an average of expression from different cell types within the endometrium. Subtle cell-specifc expression changes may not be detected and differences in cell composition between samples and across the menstrual cycle will contribute to sample variability. Power to detect tissue specific eQTLs and differences between women with and without endometriosis was limited by the sample size in this study. The statistical approaches used in this study identify the likely gene targets for specific genetic risk factors, but not the functional mechanism by which changes in gene expression may influence disease risk.

Wider Implications Of The Findings: Our results identify novel genetic variants that regulate gene expression in endometrium and the majority of these are shared across tissues. This allows analysis with large publicly available datasets to identify targets for female reproductive traits and diseases. Much larger studies will be required to identify genetic regulation of gene expression that will be specific to endometrium.

Study Funding/competing Interest(s): This work was supported by the National Health and Medical Research Council (NHMRC) under project grants GNT1026033, GNT1049472, GNT1046880, GNT1050208, GNT1105321, GNT1083405 and GNT1107258. G.W.M is supported by a NHMRC Fellowship (GNT1078399). J.Y is supported by an ARC Fellowship (FT180100186). There are no competing interests.
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http://dx.doi.org/10.1093/humrep/dez279DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7048713PMC
February 2020

Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies.

Addict Biol 2021 01 16;26(1):e12880. Epub 2020 Feb 16.

Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, RWTH Aachen University, Aachen, Germany.

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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http://dx.doi.org/10.1111/adb.12880DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7429266PMC
January 2021

Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression.

Nat Genet 2020 02 20;52(2):160-166. Epub 2020 Jan 20.

Eye Department, Greenlane Clinical Centre, Auckland District Health Board, Auckland, New Zealand.

Glaucoma, a disease characterized by progressive optic nerve degeneration, can be prevented through timely diagnosis and treatment. We characterize optic nerve photographs of 67,040 UK Biobank participants and use a multitrait genetic model to identify risk loci for glaucoma. A glaucoma polygenic risk score (PRS) enables effective risk stratification in unselected glaucoma cases and modifies penetrance of the MYOC variant encoding p.Gln368Ter, the most common glaucoma-associated myocilin variant. In the unselected glaucoma population, individuals in the top PRS decile reach an absolute risk for glaucoma 10 years earlier than the bottom decile and are at 15-fold increased risk of developing advanced glaucoma (top 10% versus remaining 90%, odds ratio = 4.20). The PRS predicts glaucoma progression in prospectively monitored, early manifest glaucoma cases (P = 0.004) and surgical intervention in advanced disease (P = 3.6 × 10). This glaucoma PRS will facilitate the development of a personalized approach for earlier treatment of high-risk individuals, with less intensive monitoring and treatment being possible for lower-risk groups.
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http://dx.doi.org/10.1038/s41588-019-0556-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8056672PMC
February 2020

Genotype-free demultiplexing of pooled single-cell RNA-seq.

Genome Biol 2019 12 19;20(1):290. Epub 2019 Dec 19.

Genome Innovation Hub, The University of Queensland, 306 Carmody Road, St Lucia, Brisbane, QLD 4072, Australia.

A variety of methods have been developed to demultiplex pooled samples in a single cell RNA sequencing (scRNA-seq) experiment which either require hashtag barcodes or sample genotypes prior to pooling. We introduce scSplit which utilizes genetic differences inferred from scRNA-seq data alone to demultiplex pooled samples. scSplit also enables mapping clusters to original samples. Using simulated, merged, and pooled multi-individual datasets, we show that scSplit prediction is highly concordant with demuxlet predictions and is highly consistent with the known truth in cell-hashing dataset. scSplit is ideally suited to samples without external genotype information and is available at: https://github.com/jon-xu/scSplit.
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http://dx.doi.org/10.1186/s13059-019-1852-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6921391PMC
December 2019

Should Genetics Now Be Considered the Pre-eminent Etiologic Factor in Endometriosis?

J Minim Invasive Gynecol 2020 02 1;27(2):280-286. Epub 2019 Nov 1.

Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, San Francisco, California (Dr. Giudice).

Endometriosis is a common, estrogen-dependent, inflammatory disorder characterized by the growth of endometrial-like tissue at extrauterine locations. Its pathogenesis and mechanisms underlying its pathophysiology are poorly understood, although genetic variation is strongly implicated in these processes. Genetic studies reveal that approximately 50% of risk for endometriosis is due to genetic factors and the other 50% likely owing to environmental factors. As with other complex diseases, genetic variants in the DNA sequence increasing endometriosis risk all have small effects, unlike most single-gene disorders. It is the combinations of these variants adding together that contribute to higher risks for individual women. In addition, recent data on disease lesions demonstrate a high frequency of somatic (likely acquired) mutations, some of which are present in the eutopic endometrium and specifically in the epithelial cell compartment, raising the possibility that abnormal epithelial progenitors in the eutopic endometrium give rise to ectopic disease. Discovery in this field is occurring at a rapid pace, and further definitions of genetic (germline) and environmental (somatic) contributions to the pathogenesis and pathophysiology of this disorder are anticipated soon. These discoveries are expected to increase diagnostic, therapeutic, and preventive strategies to minimize disease and its associated morbidities.
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http://dx.doi.org/10.1016/j.jmig.2019.10.020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863762PMC
February 2020

Associations of autozygosity with a broad range of human phenotypes.

Nat Commun 2019 10 31;10(1):4957. Epub 2019 Oct 31.

Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands.

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F) for >1.4 million individuals, we show that F is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of F are confirmed within full-sibling pairs, where the variation in F is independent of all environmental confounding.
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http://dx.doi.org/10.1038/s41467-019-12283-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823371PMC
October 2019

Genetic architecture of subcortical brain structures in 38,851 individuals.

Nat Genet 2019 11 21;51(11):1624-1636. Epub 2019 Oct 21.

Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
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http://dx.doi.org/10.1038/s41588-019-0511-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7055269PMC
November 2019

Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels.

Nat Genet 2019 10 2;51(10):1459-1474. Epub 2019 Oct 2.

Department of Neurobiology, Care Sciences and Society, Division of Family Medicine and Primary Care, Karolinska Institutet, Stockholm, Sweden.

Elevated serum urate levels cause gout and correlate with cardiometabolic diseases via poorly understood mechanisms. We performed a trans-ancestry genome-wide association study of serum urate in 457,690 individuals, identifying 183 loci (147 previously unknown) that improve the prediction of gout in an independent cohort of 334,880 individuals. Serum urate showed significant genetic correlations with many cardiometabolic traits, with genetic causality analyses supporting a substantial role for pleiotropy. Enrichment analysis, fine-mapping of urate-associated loci and colocalization with gene expression in 47 tissues implicated the kidney and liver as the main target organs and prioritized potentially causal genes and variants, including the transcriptional master regulators in the liver and kidney, HNF1A and HNF4A. Experimental validation showed that HNF4A transactivated the promoter of ABCG2, encoding a major urate transporter, in kidney cells, and that HNF4A p.Thr139Ile is a functional variant. Transcriptional coregulation within and across organs may be a general mechanism underlying the observed pleiotropy between urate and cardiometabolic traits.
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http://dx.doi.org/10.1038/s41588-019-0504-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858555PMC
October 2019

Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing.

Genome Med 2019 08 23;11(1):54. Epub 2019 Aug 23.

Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia.

Background: DNA methylation changes with age. Chronological age predictors built from DNA methylation are termed 'epigenetic clocks'. The deviation of predicted age from the actual age ('age acceleration residual', AAR) has been reported to be associated with death. However, it is currently unclear how a better prediction of chronological age affects such association.

Methods: In this study, we build multiple predictors based on training DNA methylation samples selected from 13,661 samples (13,402 from blood and 259 from saliva). We use the Lothian Birth Cohorts of 1921 (LBC1921) and 1936 (LBC1936) to examine whether the association between AAR (from these predictors) and death is affected by (1) improving prediction accuracy of an age predictor as its training sample size increases (from 335 to 12,710) and (2) additionally correcting for confounders (i.e., cellular compositions). In addition, we investigated the performance of our predictor in non-blood tissues.

Results: We found that in principle, a near-perfect age predictor could be developed when the training sample size is sufficiently large. The association between AAR and mortality attenuates as prediction accuracy increases. AAR from our best predictor (based on Elastic Net, https://github.com/qzhang314/DNAm-based-age-predictor ) exhibits no association with mortality in both LBC1921 (hazard ratio = 1.08, 95% CI 0.91-1.27) and LBC1936 (hazard ratio = 1.00, 95% CI 0.79-1.28). Predictors based on small sample size are prone to confounding by cellular compositions relative to those from large sample size. We observed comparable performance of our predictor in non-blood tissues with a multi-tissue-based predictor.

Conclusions: This study indicates that the epigenetic clock can be improved by increasing the training sample size and that its association with mortality attenuates with increased prediction of chronological age.
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http://dx.doi.org/10.1186/s13073-019-0667-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6708158PMC
August 2019

Metabolomics reveals a link between homocysteine and lipid metabolism and leukocyte telomere length: the ENGAGE consortium.

Sci Rep 2019 08 12;9(1):11623. Epub 2019 Aug 12.

Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands.

Telomere shortening has been associated with multiple age-related diseases such as cardiovascular disease, diabetes, and dementia. However, the biological mechanisms responsible for these associations remain largely unknown. In order to gain insight into the metabolic processes driving the association of leukocyte telomere length (LTL) with age-related diseases, we investigated the association between LTL and serum metabolite levels in 7,853 individuals from seven independent cohorts. LTL was determined by quantitative polymerase chain reaction and the levels of 131 serum metabolites were measured with mass spectrometry in biological samples from the same blood draw. With partial correlation analysis, we identified six metabolites that were significantly associated with LTL after adjustment for multiple testing: lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0, p-value = 7.1 × 10), methionine (p-value = 9.2 × 10), tyrosine (p-value = 2.1 × 10), phosphatidylcholine diacyl C32:1 (PC aa C32:1, p-value = 2.4 × 10), hydroxypropionylcarnitine (C3-OH, p-value = 2.6 × 10), and phosphatidylcholine acyl-alkyl C38:4 (PC ae C38:4, p-value = 9.0 × 10). Pathway analysis showed that the three phosphatidylcholines and methionine are involved in homocysteine metabolism and we found supporting evidence for an association of lipid metabolism with LTL. In conclusion, we found longer LTL associated with higher levels of lysoPC a C17:0 and PC ae C38:4, and with lower levels of methionine, tyrosine, PC aa C32:1, and C3-OH. These metabolites have been implicated in inflammation, oxidative stress, homocysteine metabolism, and in cardiovascular disease and diabetes, two major drivers of morbidity and mortality.
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http://dx.doi.org/10.1038/s41598-019-47282-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6690953PMC
August 2019

Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa.

Nat Genet 2019 08 15;51(8):1207-1214. Epub 2019 Jul 15.

Clinical Genetics Unit, Department of Woman and Child Health, University of Padova, Padova, Italy.

Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness, affecting 0.9-4% of women and 0.3% of men, with twin-based heritability estimates of 50-60%. Mortality rates are higher than those in other psychiatric disorders, and outcomes are unacceptably poor. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI) and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes.
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http://dx.doi.org/10.1038/s41588-019-0439-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6779477PMC
August 2019