Publications by authors named "Marco Brumat"

26 Publications

  • Page 1 of 1

Genetic insights into biological mechanisms governing human ovarian ageing.

Nature 2021 08 4;596(7872):393-397. Epub 2021 Aug 4.

Genome Integrity and Instability Group, Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.

Reproductive longevity is essential for fertility and influences healthy ageing in women, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41586-021-03779-7DOI Listing
August 2021

Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color.

Sci Adv 2021 Mar 10;7(11). Epub 2021 Mar 10.

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.

Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/sciadv.abd1239DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7946369PMC
March 2021

F cell numbers are associated with an X-linked genetic polymorphism and correlate with haematological parameters in patients with sickle cell disease.

Br J Haematol 2020 12 19;191(5):888-896. Epub 2020 Oct 19.

Muhimbili Sickle Cell Programme, Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania.

Patients with sickle cell disease (SCD) with high fetal haemoglobin (HbF) tend to have a lower incidence of complications and longer survival due to inhibition of deoxyhaemoglobin S (HbS) polymerisation by HbF. HbF-containing cells, namely F cells, are strongly influenced by genetic factors. We measured the percentage of F cells (Fcells%) in 222 patients with SCD to evaluate the association of (i) Fcells% with genetic HbF-modifier variants and (ii) Fcells% with haematological parameters. There was a different distribution of Fcells% in females compared to males. The association of the B-cell lymphoma/leukaemia 11A (BCL11A) locus with Fcells% (β = 8·238; P < 0·001) and with HbF% (β = 2·490; P < 0·001) was significant. All red cell parameters except for Hb and mean corpuscular Hb concentration levels in males and females were significantly different. The Fcells% was positively associated with mean cell Hb, mean cell volume and reticulocytes. To explain the significant gender difference in Fcells%, we tested for associations with single nucleotide polymorphisms on the X chromosomal region Xp22.2, where a genetic determinant of HbF had been previously hypothesised. We found in males a significant association with a SNP in FERM and PDZ domain-containing protein 4 (FRMPD4) and adjacent to male-specific lethal complex subunit 3 (MSL3). Thus, we have identified an X-linked locus that could account for a significant fraction of the Fcells% variation in patients with SCD.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/bjh.17102DOI Listing
December 2020

Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.

Mol Psychiatry 2021 Jun 5;26(6):2111-2125. Epub 2020 May 5.

Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA.

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41380-020-0719-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641978PMC
June 2021

A bird's-eye view of Italian genomic variation through whole-genome sequencing.

Eur J Hum Genet 2020 04 29;28(4):435-444. Epub 2019 Nov 29.

Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy.

The genomic variation of the Italian peninsula populations is currently under characterised: the only Italian whole-genome reference is represented by the Tuscans from the 1000 Genome Project. To address this issue, we sequenced a total of 947 Italian samples from three different geographical areas. First, we defined a new Italian Genome Reference Panel (IGRP1.0) for imputation, which improved imputation accuracy, especially for rare variants, and we tested it by GWAS analysis on red blood traits. Furthermore, we extended the catalogue of genetic variation investigating the level of population structure, the pattern of natural selection, the distribution of deleterious variants and occurrence of human knockouts (HKOs). Overall the results demonstrate a high level of genomic differentiation between cohorts, different signatures of natural selection and a distinctive distribution of deleterious variants and HKOs, confirming the necessity of distinct genome references for the Italian population.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41431-019-0551-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080768PMC
April 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-019-12283-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823371PMC
October 2019

Genome-wide association meta-analysis identifies five novel loci for age-related hearing impairment.

Sci Rep 2019 10 23;9(1):15192. Epub 2019 Oct 23.

Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy.

Previous research has shown that genes play a substantial role in determining a person's susceptibility to age-related hearing impairment. The existing studies on this subject have different results, which may be caused by difficulties in determining the phenotype or the limited number of participants involved. Here, we have gathered the largest sample to date (discovery n = 9,675; replication n = 10,963; validation n = 356,141), and examined phenotypes that represented low/mid and high frequency hearing loss on the pure tone audiogram. We identified 7 loci that were either replicated and/or validated, of which 5 loci are novel in hearing. Especially the ILDR1 gene is a high profile candidate, as it contains our top SNP, is a known hearing loss gene, has been linked to age-related hearing impairment before, and in addition is preferentially expressed within hair cells of the inner ear. By verifying all previously published SNPs, we can present a paper that combines all new and existing findings to date, giving a complete overview of the genetic architecture of age-related hearing impairment. This is of importance as age-related hearing impairment is highly prevalent in our ageing society and represents a large socio-economic burden.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-019-51630-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811684PMC
October 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-019-0504-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6858555PMC
October 2019

Effects of Calcium, Magnesium, and Potassium Concentrations on Ventricular Repolarization in Unselected Individuals.

J Am Coll Cardiol 2019 06;73(24):3118-3131

Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California.

Background: Subclinical changes on the electrocardiogram are risk factors for cardiovascular mortality. Recognition and knowledge of electrolyte associations in cardiac electrophysiology are based on only in vitro models and observations in patients with severe medical conditions.

Objectives: This study sought to investigate associations between serum electrolyte concentrations and changes in cardiac electrophysiology in the general population.

Methods: Summary results collected from 153,014 individuals (54.4% women; mean age 55.1 ± 12.1 years) from 33 studies (of 5 ancestries) were meta-analyzed. Linear regression analyses examining associations between electrolyte concentrations (mmol/l of calcium, potassium, sodium, and magnesium), and electrocardiographic intervals (RR, QT, QRS, JT, and PR intervals) were performed. The study adjusted for potential confounders and also stratified by ancestry, sex, and use of antihypertensive drugs.

Results: Lower calcium was associated with longer QT intervals (-11.5 ms; 99.75% confidence interval [CI]: -13.7 to -9.3) and JT duration, with sex-specific effects. In contrast, higher magnesium was associated with longer QT intervals (7.2 ms; 99.75% CI: 1.3 to 13.1) and JT. Lower potassium was associated with longer QT intervals (-2.8 ms; 99.75% CI: -3.5 to -2.0), JT, QRS, and PR durations, but all potassium associations were driven by use of antihypertensive drugs. No physiologically relevant associations were observed for sodium or RR intervals.

Conclusions: The study identified physiologically relevant associations between electrolytes and electrocardiographic intervals in a large-scale analysis combining cohorts from different settings. The results provide insights for further cardiac electrophysiology research and could potentially influence clinical practice, especially the association between calcium and QT duration, by which calcium levels at the bottom 2% of the population distribution led to clinically relevant QT prolongation by >5 ms.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jacc.2019.03.519DOI Listing
June 2019

A catalog of genetic loci associated with kidney function from analyses of a million individuals.

Nat Genet 2019 06 31;51(6):957-972. Epub 2019 May 31.

Diabetes and Cardiovascular Disease-Genetic Epidemiology, Department of Clincial Sciences in Malmö, Lund University, Malmö, Sweden.

Chronic kidney disease (CKD) is responsible for a public health burden with multi-systemic complications. Through trans-ancestry meta-analysis of genome-wide association studies of estimated glomerular filtration rate (eGFR) and independent replication (n = 1,046,070), we identified 264 associated loci (166 new). Of these, 147 were likely to be relevant for kidney function on the basis of associations with the alternative kidney function marker blood urea nitrogen (n = 416,178). Pathway and enrichment analyses, including mouse models with renal phenotypes, support the kidney as the main target organ. A genetic risk score for lower eGFR was associated with clinically diagnosed CKD in 452,264 independent individuals. Colocalization analyses of associations with eGFR among 783,978 European-ancestry individuals and gene expression across 46 human tissues, including tubulo-interstitial and glomerular kidney compartments, identified 17 genes differentially expressed in kidney. Fine-mapping highlighted missense driver variants in 11 genes and kidney-specific regulatory variants. These results provide a comprehensive priority list of molecular targets for translational research.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-019-0407-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6698888PMC
June 2019

Next Generation Sequencing and Animal Models Reveal as a New Gene Involved in Human Age-Related Hearing Loss.

Front Genet 2019 26;10:142. Epub 2019 Feb 26.

Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy.

Age-related hearing loss (ARHL) is the most common sensory impairment in the elderly affecting millions of people worldwide. To shed light on the genetics of ARHL, a large cohort of 464 Italian patients has been deeply characterized at clinical and molecular level. In particular, 46 candidate genes, selected on the basis of genome-wide association studies (GWAS), animal models and literature updates, were analyzed by targeted re-sequencing. After filtering and prioritization steps, has been identified as a strong candidate and then validated by " and studies. Briefly, a rare (MAF: 2.886e-5) missense variant c.539G > A, p.(R180Q) was detected in two unrelated male patients affected by ARHL characterized by a severe to profound high-frequency hearing loss. The variant, predicted as damaging, was not present in healthy matched controls. Protein modeling confirmed the pathogenic effect of p.(R180Q) variant on protein's structure leading to a change in the total number of hydrogen bonds. hybridization showed expression in zebrafish inner ear. A zebrafish knock-in model, generated by CRISPR-Cas9 technology, revealed a reduced auditory response at all frequencies in mutants compared to and animals. Moreover, a significant reduction (5.8%) in the total volume of the saccular otolith (which is responsible for sound detection) was observed in compared to ( = 0.0014), while the utricular otolith, necessary for balance, was not affected in agreement with the human phenotype. Overall, these data strongly support the role of gene in the pathogenesis of ARHL opening new perspectives in terms of diagnosis, prevention and treatment.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fgene.2019.00142DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399162PMC
February 2019

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Nat Commun 2019 01 22;10(1):376. Epub 2019 Jan 22.

Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, 01246903, SP, Brazil.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-08008-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342931PMC
January 2019

Genomic Studies in a Large Cohort of Hearing Impaired Italian Patients Revealed Several New Alleles, a Rare Case of Uniparental Disomy (UPD) and the Importance to Search for Copy Number Variations.

Front Genet 2018 21;9:681. Epub 2018 Dec 21.

Department of Medicine, Surgery and Health Sciences, University of Trieste, Trieste, Italy.

Hereditary hearing loss (HHL) is a common disorder characterized by a huge genetic heterogeneity. The definition of a correct molecular diagnosis is essential for proper genetic counseling, recurrence risk estimation, and therapeutic options. From 20 to 40% of patients carry mutations in gene, thus, in more than half of cases it is necessary to look for causative variants in the other genes so far identified (~100). In this light, the use of next-generation sequencing technologies has proved to be the best solution for mutational screening, even though it is not always conclusive. Here we describe a combined approach, based on targeted re-sequencing (TRS) of 96 HHL genes followed by high-density SNP arrays, aimed at the identification of the molecular causes of non-syndromic HHL (NSHL). This strategy has been applied to study 103 Italian unrelated cases, negative for mutations in , and led to the characterization of 31% of them (i.e., 37% of familial and 26.3% of sporadic cases). In particular, TRS revealed and genes as major players in the Italian population. Furthermore, two missense variants in 1 have been identified and investigated through protein modeling and molecular dynamics simulations, confirming their likely pathogenic effect. Among the selected patients analyzed by SNP arrays (negative to TRS, or with a single variant in a recessive gene) a molecular diagnosis was reached in ~36% of cases, highlighting the importance to look for large insertions/deletions. Moreover, copy number variants analysis led to the identification of the first case of uniparental disomy involving gene. Overall, taking into account the contribution of , plus the results from TRS and SNP arrays, it was possible to reach a molecular diagnosis in ~51% of NSHL cases. These data proved the usefulness of a combined approach for the analysis of NSHL and for the definition of the epidemiological picture of HHL in the Italian population.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fgene.2018.00681DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6309105PMC
December 2018

Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.

Nat Genet 2018 10 17;50(10):1412-1425. Epub 2018 Sep 17.

Laboratory of Genetics and Genomics, NIA/NIH, Baltimore, MD, USA.

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-018-0205-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284793PMC
October 2018

Cx26 partial loss causes accelerated presbycusis by redox imbalance and dysregulation of Nfr2 pathway.

Redox Biol 2018 10 7;19:301-317. Epub 2018 Aug 7.

CNR Institute of Cell Biology and Neurobiology, Monterotondo 00015, Italy; University of Padova, Department of Physics and Astronomy "G. Galilei", Padova, Italy. Electronic address:

Mutations in GJB2, the gene that encodes connexin 26 (Cx26), are the most common cause of sensorineural hearing impairment. The truncating variant 35delG, which determines a complete loss of Cx26 protein function, is the prevalent GJB2 mutation in several populations. Here, we generated and analyzed Gjb2 mice as a model of heterozygous human carriers of 35delG. Compared to control mice, auditory brainstem responses (ABRs) and distortion product otoacoustic emissions (DPOAEs) worsened over time more rapidly in Gjb2 mice, indicating they were affected by accelerated age-related hearing loss (ARHL), or presbycusis. We linked causally the auditory phenotype of Gjb2 mice to apoptosis and oxidative damage in the cochlear duct, reduced release of glutathione from connexin hemichannels, decreased nutrient delivery to the sensory epithelium via cochlear gap junctions and deregulated expression of genes that are under transcriptional control of the nuclear factor erythroid 2-related factor 2 (Nrf2), a pivotal regulator of tolerance to redox stress. Moreover, a statistically significant genome-wide association with two genes (PRKCE and TGFB1) related to the Nrf2 pathway (p-value < 4 × 10) was detected in a very large cohort of 4091 individuals, originating from Europe, Caucasus and Central Asia, with hearing phenotype (including 1076 presbycusis patients and 1290 healthy matched controls). We conclude that (i) elements of the Nrf2 pathway are essential for hearing maintenance and (ii) their dysfunction may play an important role in the etiopathogenesis of human presbycusis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.redox.2018.08.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6129666PMC
October 2018

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.

PLoS One 2018 18;13(6):e0198166. Epub 2018 Jun 18.

Icelandic Heart Association, Kopavogur, Iceland.

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0198166PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005576PMC
January 2019

Whole-genome sequencing reveals new insights into age-related hearing loss: cumulative effects, pleiotropy and the role of selection.

Eur J Hum Genet 2018 08 30;26(8):1167-1179. Epub 2018 Apr 30.

Medical Sciences, Chirurgical and Health Department, University of Trieste, Trieste, Italy.

Age-related hearing loss (ARHL) is the most common sensory disorder in the elderly. Although not directly life threatening, it contributes to loss of autonomy and is associated with anxiety, depression and cognitive decline. To search for genetic risk factors underlying ARHL, a large whole-genome sequencing (WGS) approach has been carried out in a cohort of 212 cases and controls, both older than 50 years to select genes characterized by a burden of variants specific to cases or controls. Accordingly, the total variation load per gene was compared and two groups were detected: 375 genes more variable in cases and 371 more variable in controls. In both cases, Gene Ontology analysis showed that the largest enrichment for biological processes (fold > 5, p-value = 0.042) was the "sensory perception of sound", suggesting cumulative genetic effects were involved. Replication confirmed 141 genes, while additional analysis based on natural selection led to a prioritization of 21 genes. The majority of them (20 out of 21) showed positive expression in mouse cochlea cDNA and were associated with two functional pathways. Among them, two genes were previously associated with hearing (CSMD1 and PTRPD) and re-sequenced in a large Italian cohort of ARHL patients (N = 389). Results led to the identification of six coding variants not detected in cases so far, suggesting a possible protective role, which requires investigation. In conclusion, we show that this multistep strategy (WGS, selection, expression, pathway analysis and targeted re-sequencing) can provide major insights into the molecular characterization of complex diseases such as ARHL.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41431-018-0126-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6057993PMC
August 2018

Genome-wide association meta-analysis of individuals of European ancestry identifies new loci explaining a substantial fraction of hair color variation and heritability.

Nat Genet 2018 05 16;50(5):652-656. Epub 2018 Apr 16.

Centre for Ophthalmology and Visual Science, University of Western Australia, Lions Eye Institute, Perth, WA, Australia.

Hair color is one of the most recognizable visual traits in European populations and is under strong genetic control. Here we report the results of a genome-wide association study meta-analysis of almost 300,000 participants of European descent. We identified 123 autosomal and one X-chromosome loci significantly associated with hair color; all but 13 are novel. Collectively, single-nucleotide polymorphisms associated with hair color within these loci explain 34.6% of red hair, 24.8% of blond hair, and 26.1% of black hair heritability in the study populations. These results confirm the polygenic nature of complex phenotypes and improve our understanding of melanin pigment metabolism in humans.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-018-0100-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5935237PMC
May 2018

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 05;50(5):766-767

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-018-0082-3DOI Listing
May 2018

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 01 22;50(1):26-41. Epub 2017 Dec 22.

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-017-0011-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945951PMC
January 2018

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Hypertension 2017 Jul 24. Epub 2017 Jul 24.

From the Department of Health Sciences (L.V.W., A.M.E., N. Shrine, C.B., T.B., M.D.T.), and Department of Cardiovascular Sciences and NIHR Leicester Biomedical Research Centre (C.P.N., P.S.B., N.J.S.), University of Leicester, United Kingdom; Department of Epidemiology (A.V., P.J.v.d.M., I.M.N., H. Snieder), Division of Nephrology, Department of Internal Medicine (M.H.d.B., M.A.S.), Interdisciplinary Center Psychopathology and Emotion Regulation (IPCE) (A.J.O., H.R., C.A.H.), Department of Genetics, (M.S.), and Department of Cardiology (P.v.d.H.), University of Groningen, University Medical Center Groningen, The Netherlands; Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Iran (A.V.); Department of Psychiatry, VU University Medical Center, Neuroscience Campus Amsterdam, The Netherlands (R. Jansen); Hebrew SeniorLife, Harvard Medical School, Boston, MA (R. Joehanes); National Heart, Lung and Blood Institute's Framingham Heart Study, MA (R. Joehanes, A.D.J., M. Larson); Institute of Psychiatry, Psychology and Neuroscience (P.F.O.), and Department of Twin Research and Genetic Epidemiology (M.M., C. Menni, T.D.S.), King's College London, United Kingdom; Clinical Pharmacology, William Harvey Research Institute (C.P.C., H.R.W., M.R.B., M. Brown, B.M., M.R., P.B.M., M.J.C.) and NIHR Barts Cardiovascular Biomedical Research Unit (C.P.C., H.R.W., M.R.B., M. Brown, P.B.M., M.J.C.), Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom; Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA (L.M.R., F.G., P.M.R., D.I.C.); Department of Epidemiology (G.C.V., A. Hofman, A.G.U., O.H.F.), Genetic Epidemiology Unit, Department of Epidemiology (N.A., B.A.O., C.M.v.D.), and Department of Internal Medicine (A.G.U.), Erasmus MC, Rotterdam, The Netherlands; Department of Biological Psychology, Vrije Universiteit, Amsterdam, EMGO+ Institute, VU University Medical Center, The Netherlands (J.-J.H., E.J.d.G., G.W., D.I.B.); Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden (R.J.S., M. Frånberg, A. Hamsten); Centre for Molecular Medicine, Karolinska Universitetsjukhuset, Solna, Sweden (R.J.S., M. Frånberg, A. Hamsten); Estonian Genome Center (T.E., E.O., A. Metspalu), Institute of Biomedicine and Translational Medicine (S.S., M. Laan), and Estonian Genome Center (M.P.), University of Tartu, Estonia; Divisions of Endocrinology/Children's Hospital, Boston, MA (T.E.); Broad Institute of Harvard and MIT, Cambridge, MA (T.E., C.M.L., C.N.-C.); Center for Complex Disease Genomics, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD (D.E.A., P.N., A. Chakravarti, G.B.E.); The Population Science Branch, Division of Intramural Research, National Heart Lung and Blood Institute (S.-J.H., D.L.), Laboratory of Neurogenetics, National Institute on Aging (M.A.N.), Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute (F.C.), and Center for Information Technology (Y.D., P.J.M., Q.T.N.), National Institutes of Health, Bethesda, MD; The Framingham Heart Study, Framingham, MA (S.-J.H., D.L.); The Institute for Translational Genomics and Population Sciences, Department of Pediatrics (X.G., J.Y.), and The Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine (J.I.R.), LABioMed at Harbor-UCLA Medical Center, Torrance, CA; Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland (Z.K., M. Bochud); Swiss Institute of Bioinformatics, Lausanne, Switzerland (Z.K.); Department of Cardiology (S. Trompet, J.W.J.) Department of Gerontology and Geriatrics (S. Trompet), Department of Clinical Epidemiology (R.L.-G., R.d.M., D.O.M.-K.), Department of Molecular Epidemiology (J.D.), and Department of Public Health and Primary Care (D.O.M.-K.), Leiden University Medical Center, The Netherlands; Institute for Community Medicine (A.T.), Department of Internal Medicine B (M.D.), and Interfaculty Institute for Genetics and Functional Genomics (U.V.), University Medicine Greifswald, Germany; DZHK (German Centre for Cardiovascular Research), partner site Greifswald, Germany (A.T., M.D., U.V.); Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany (J.S.R., A. Peters); Cardiovascular Health Research Unit, Department of Medicine (J.C.B., B.M.P.) and Departments of Biostatistics (K.R.), Epidemiology (B.M.P.), and Health Services (B.M.P.), University of Washington, Seattle; Icelandic Heart Association, Kopavogur, Iceland (A.V.S., V. Gudnason); Faculty of Medicine, University of Iceland, Reykjavik, Iceland (A.V.S., V. Gudnason); Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland (L.-P.L., T.L.); Department of Clinical Chemistry, Faculty of Medicine and Life Sciences, University of Tampere, Finland (L.-P.L., T.L.); Wellcome Trust Centre for Human Genetics (A. Mahajan, A.G., M. Farrall, T.F., C.M.L., H.W., A.P.M.), and Division of Cardiovascular Medicine, Radcliffe Department of Medicine (A.G., M. Farrall, H.W.), University of Oxford, United Kingdom; MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, United Kingdom (N.J.W., J.L., C.L., R.J.F.L., R.A.S., J.H.Z.); Clinical Division of Neurogeriatrics, Department of Neurology (E.H., R. Schmidt), Institute of Medical Informatics, Statistics and Documentation (E.H.), and Department of Neurology (H. Schmidt), Medical University Graz, Austria; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics (P.K.J., H.C., I.R., S.W., J.F.W.), Centre for Cognitive Ageing and Cognitive Epidemiology (L.M.L., S.E.H., G.D., A.J.G., D.C.M.L., J.M.S., I.J.D.), Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine (A. Campbell), Generation Scotland, Centre for Genomic and Experimental Medicine (A. Campbell, S.P., C.H.), Department of Psychology (G.D., D.C.M.L., A. Pattie, I.J.D.), Alzheimer Scotland Dementia Research Centre (J.M.S.), and Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine (C.H.), University of Edinburgh, Scotland, United Kingdom; Department of Health (K.K., A.S.H., T. Niiranen, P.J., A.J., S. Koskinen, P.K., V.S., M.P.), and Chronic Disease Prevention Unit (J.T.), National Institute for Health and Welfare (THL), Helsinki, Finland; Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milano, Italy (M.T., C.M.B., C.F.S., D.T.); Data Tecnica International, Glen Echo, MD (M.A.N.); Medical Genetics, IRCCS-Burlo Garofolo Children Hospital, Trieste, Italy (D.V., G.G., P.G.); Department of Medical, Surgical and Health Sciences, University of Trieste, Italy (D.V., I.G., M. Brumat, M. Cocca, A. Morgan, G.G., P.G.); Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy (F.D.G.M., P.P.P., A.S.P., A.A.H.); Department of Genetics and Genomic Sciences (K.L.A.), The Charles Bronfman Institute for Personalized Medicine (Y.L., E.P.B., R.J.F.L.), and Mindich Child health Development Institute (R.J.F.L.), Icahn School of Medicine at Mount Sinai, New York; Cardiovascular Epidemiology and Genetics, IMIM, and CIBERCV, Barcelona, Spain (J. Marrugat, R.E.); Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, Napoli, Italy (D.R., T. Nutile, R. Sorice, M. Ciullo); Department of Psychiatry, Royal College of Surgeons in Ireland, Education and Research Centre, Beaumont Hospital, Dublin (L.M.L.); UCD Conway Institute, Centre for Proteome Research (L.M.L.), and School of Medicine, Conway Institute (D.C.S.), University College Dublin, Belfield, Ireland; Department of Immunology, Genetics and Pathology, Uppsala Universitet, Science for Life Laboratory, Sweden (S.E., Å. Johansson, U.G.); Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor (A.U.J., M. Boehnke); NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester United Kingdom (C.P.N., P.S.B., N.J.S.); MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine (J.E.H., V.V., J. Marten, A.F.W., J.F.W.), and Medical Genetics Section, Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine (S.E.H.), University of Edinburgh, Western General Hospital, Scotland, United Kingdom; Department of Epidemiology and Biostatistics, School of Public Health (W.Z., E.E., J.C.C., H.G., B.L., I.T., A.-C.V.), MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health (M.-R.J., P.E.), School of Public Health (N.P.), International Centre for Circulatory Health (S. Thom), and National Heart and Lung Institute (P.S.), Imperial College London, United Kingdom; Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, United Kingdom (W.Z., J.C.C., J.S.K.); Department of Medical Biology, Faculty of Medicine, University of Split, Croatia (T.Z.); Department of Hygiene and Epidemiology, University of Ioannina Medical School, Greece (E.E.); Medical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Scotland, United Kingdom (N. Shah, A.S.F.D., C.N.A.P.); Department of Pharmacy, COMSATS Institute of Information Technology, Abbottabad, Pakistan (N. Shah); National Institute for Health Research Biomedical Research Centre, London, United Kingdom (M.M.); Department of Human Genetics, Wellcome Trust Sanger Institute, United Kingdom (B.P.P., E.Z.); INSERM U 1219, Bordeaux Population Health Center, France (G.C., C.T., S.D.); Bordeaux University, France (G.C., C.T., S.D.); Hunter Medical Research Institute, New Lambton, NSW, Australia (C.O., E.G.H., R. Scott, J.A.); Center for Statistical Genetics, Department of Biostatistics, Ann Arbor, MI (G.A.); Department of Genetics and Molecular Biology, Isfahan University of Medical Sciences, Iran (M.A.); Busselton Population Medical Research Institute, Western Australia (J.B., J.H.); PathWest Laboratory Medicine of Western Australia, Nedlands (J.B., J.H.); School of Pathology and Laboratory Medicine (J.B., J.H.), School of Population and Global Health (J.H.), and School of Medicine and Pharmacology (A. James), The University of Western Australia, Nedlands; Imperial College Healthcare NHS Trust, London, United Kingdom (J.C.C., J.S.K.); University of Dundee, Ninewells Hospital & Medical School, United Kingdom (J.C.); Institute of Genetic Medicine (H.J.C.), and Institute of Health and Society (C. Mamasoula), Newcastle University, Newcastle upon Tyne, United Kingdom; Department of Pathology, Amsterdam Medical Center, The Netherlands (J.J.D.); Department of Numerical Analysis and Computer Science, Stockholm University, Sweden (M. Frånberg); Department of Public Health and Caring Sciences, Geriatrics, Uppsala, Sweden (V. Giedraitis); Helmholtz Zentrum Muenchen, Deutsches Forschungszentrum fuer Gesundheit und Umwelt (GmbH), Neuherberg, Germany (C.G.); Department of Psychology, School of Social Sciences, Heriot-Watt University, Edinburgh, United Kingdom (A.J.G.); Intramural Research Program, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging (T.B.H., L.J.L.); Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA (A. Hofman); Center For Life-Course Health Research (M.-R.J.), and Biocenter Oulu (M.-R.J.), University of Oulu, Finland; Unit of Primary Care, Oulu University Hospital, Finland (M.-R.J.); National Heart, Lung and Blood Institute, Cardiovascular Epidemiology and Human Genomics Branch, Bethesda, MD (A.D.J.); Department of Clinical Physiology, Tampere University Hospital, Finland (M.K.); Department of Clinical Physiology, Faculty of Medicine and Life Sciences, University of Tampere, Finland (M.K.); Cardiovascular Research Center (S. Kathiresan, C.N.-C.); Center for Human Genetics (S. Kathiresan), and Center for Human Genetic Research (C.N.-C.), Massachusetts General Hospital, Boston; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA (S. Kathiresan, C.N.-C.); Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge, United Kingdom (K.-T.K.); Department of Public Health, Faculty of Medicine, University of Split, Croatia (I.K., O.P.); Cardiology, Department of Specialties of Medicine, Geneva University Hospital, Switzerland (L. Lin, F.M., G.B.E.); Department of Medical Sciences, Cardiovascular Epidemiology (L. Lind, J.S.), and Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory (E.I.), Uppsala University, Sweden; Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands (Y.M., B.W.J.H.P.); School of Molecular, Genetic and Population Health Sciences, University of Edinburgh, Medical School, Teviot Place, Scotland, United Kingdom (A.D.M.); Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston (A.C.M.); British Heart Foundation Glasgow Cardiovascular Research Centre, Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences (S.P.), and Institute of Cardiovascular and Medical Sciences, Faculty of Medicine (D.J.S.), University of Glasgow, United Kingdom; Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland (A. Palotie, S.R., A.-P.S., M.P.); Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada (G.P., S. Thériault); Department of Neurology, General Central Hospital, Bolzano, Italy (P.P.P.); Department of Neurology, University of Lübeck, Germany (P.P.P.); Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Finland (O.T.R.); Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Finland (O.T.R.); Department of Cardiology, Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China (M.R.); Harvard Medical School, Boston, MA (P.M.R., D.I.C.); Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste, Italy (A.R.); Institute of Molecular Biology and Biochemistry, Centre for Molecular Medicine, Medical University of Graz, Austria (Y.S., H. Schmidt); INSERM U1078, Etablissement Français du Sang, Brest Cedex, France (A.S.P.); Faculty of Health, University of Newcastle, Callaghan, NSW, Australia (R. Scott, J.A.); John Hunter Hospital, New Lambton, NSW, Australia (R. Scott, J.A.); The New York Academy of Medicine, New York (D.S.); IRCCS Neuromed, Pozzilli, Isernia, Italy (R. Sorice, M. Ciullo); Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland (A.S.); Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA (K.D.T.); Division of Genetic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA (K.D.T.); Department of Public Health (C.T.), and Department of Neurology (S.D.), Bordeaux University Hospital, France; Department of Internal Medicine, Lausanne University Hospital, CHUV, Switzerland (P.V.); Population Health Research Institute, McMaster University, Hamilton Ontario, Canada (D.C.); National Heart and Lung Institute, Imperial College London, Hammersmith Hospital Campus, United Kingdom (J.S.K.); Dasman Diabetes Institute, Kuwait (J.T.); Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia (J.T.); Department of Neurosciences and Preventive Medicine, Danube-University Krems, Austria (J.T.); Division of Cardiovascular Sciences, The University of Manchester and Central Manchester University Hospitals NHS Foundation Trust, United Kingdom (B.D.K.); Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem (Y.M.L.); Kaiser Permanent Washington Health Research Institute, Seattle, WA (B.M.P.); Institute of Physiology, University Medicine Greifswald, Karlsburg, Germany (R.R); Department of Pulmonary Physiology and Sleep, Sir Charles Gairdner Hospital, Nedlands, Western Australia (A. James); Population Health Research Institute, St George's, University of London, United Kingdom (D.P.S.); Department of Medicine, Columbia University Medical Center, New York (W.P.); Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, CA (E.I.); Data Science Institute and Lancaster Medical School, Lancaster University, United Kingdom (J.K.); and Department of Biostatistics, University of Liverpool, United Kingdom (A.P.M.).

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near , , , , , and , and provide new replication evidence for a further 2 signals in and Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/HYPERTENSIONAHA.117.09438DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783787PMC
July 2017

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

Nat Genet 2017 Jun 24;49(6):834-841. Epub 2017 Apr 24.

Institute of Genetics and Biophysics, CNR, Naples, Italy.

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.3841DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841952PMC
June 2017
-->