132 research outputs found
Publisher correction: Genome-wide association of polycystic ovary syndrome implicates alterations in gonadotropin secretion in European ancestry populations.
An amendment to this paper has been published and can be accessed via a link at the top of the paper
Testing the role of predicted gene knockouts in human anthropometric trait variation
National Heart, Lung, and Blood Institute (NHLBI)
S.L. is funded by a Canadian Institutes of Health Research
Banting doctoral scholarship. G.L. is funded by Genome Canada
and Génome Québec; the Canada Research Chairs program; and
the Montreal Heart Institute Foundation. C.M.L. is supported by
Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A);
and the Li Ka Shing Foundation. N.S. is funded by National Institutes
of Health (grant numbers HL088456, HL111089, HL116747).
The Mount Sinai BioMe Biobank Program is supported by the Andrea
and Charles Bronfman Philanthropies. GO ESP is supported
by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO,
RC2 HL-102924 to WHISP). The ESP exome sequencing was
performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL-
102926 to SeattleGO). EGCUT work was supported through the
Estonian Genome Center of University of Tartu by the Targeted
Financing from the Estonian Ministry of Science and Education
(grant number SF0180142s08); the Development Fund of the University
of Tartu (grant number SP1GVARENG); the European Regional
Development Fund to the Centre of Excellence in
Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and
through FP7 (grant number 313010). EGCUT were further supported
by the US National Institute of Health (grant number
R01DK075787). A.K.M. was supported by an American Diabetes
Association Mentor-Based Postdoctoral Fellowship (#7-12-MN-
02). The BioVU dataset used in the analyses described were obtained
from Vanderbilt University Medical Centers BioVU which
is supported by institutional funding and by the Vanderbilt CTSA
grant ULTR000445 from NCATS/NIH. Genome-wide genotyping
was funded by NIH grants RC2GM092618 from NIGMS/OD and
U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access
publication charges for this article was provided by a block
grant from Research Councils UK to the University of Cambridge
Testing the role of predicted gene knockouts in human anthropometric trait variation
National Heart, Lung, and Blood Institute (NHLBI)
S.L. is funded by a Canadian Institutes of Health Research
Banting doctoral scholarship. G.L. is funded by Genome Canada
and Génome Québec; the Canada Research Chairs program; and
the Montreal Heart Institute Foundation. C.M.L. is supported by
Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A);
and the Li Ka Shing Foundation. N.S. is funded by National Institutes
of Health (grant numbers HL088456, HL111089, HL116747).
The Mount Sinai BioMe Biobank Program is supported by the Andrea
and Charles Bronfman Philanthropies. GO ESP is supported
by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO,
RC2 HL-102924 to WHISP). The ESP exome sequencing was
performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL-
102926 to SeattleGO). EGCUT work was supported through the
Estonian Genome Center of University of Tartu by the Targeted
Financing from the Estonian Ministry of Science and Education
(grant number SF0180142s08); the Development Fund of the University
of Tartu (grant number SP1GVARENG); the European Regional
Development Fund to the Centre of Excellence in
Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and
through FP7 (grant number 313010). EGCUT were further supported
by the US National Institute of Health (grant number
R01DK075787). A.K.M. was supported by an American Diabetes
Association Mentor-Based Postdoctoral Fellowship (#7-12-MN-
02). The BioVU dataset used in the analyses described were obtained
from Vanderbilt University Medical Centers BioVU which
is supported by institutional funding and by the Vanderbilt CTSA
grant ULTR000445 from NCATS/NIH. Genome-wide genotyping
was funded by NIH grants RC2GM092618 from NIGMS/OD and
U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access
publication charges for this article was provided by a block
grant from Research Councils UK to the University of Cambridge
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Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.
Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants
Testing the role of predicted gene knockouts in human anthropometric trait variation
National Heart, Lung, and Blood Institute (NHLBI)
S.L. is funded by a Canadian Institutes of Health Research
Banting doctoral scholarship. G.L. is funded by Genome Canada
and Génome Québec; the Canada Research Chairs program; and
the Montreal Heart Institute Foundation. C.M.L. is supported by
Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A);
and the Li Ka Shing Foundation. N.S. is funded by National Institutes
of Health (grant numbers HL088456, HL111089, HL116747).
The Mount Sinai BioMe Biobank Program is supported by the Andrea
and Charles Bronfman Philanthropies. GO ESP is supported
by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO,
RC2 HL-102924 to WHISP). The ESP exome sequencing was
performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL-
102926 to SeattleGO). EGCUT work was supported through the
Estonian Genome Center of University of Tartu by the Targeted
Financing from the Estonian Ministry of Science and Education
(grant number SF0180142s08); the Development Fund of the University
of Tartu (grant number SP1GVARENG); the European Regional
Development Fund to the Centre of Excellence in
Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and
through FP7 (grant number 313010). EGCUT were further supported
by the US National Institute of Health (grant number
R01DK075787). A.K.M. was supported by an American Diabetes
Association Mentor-Based Postdoctoral Fellowship (#7-12-MN-
02). The BioVU dataset used in the analyses described were obtained
from Vanderbilt University Medical Centers BioVU which
is supported by institutional funding and by the Vanderbilt CTSA
grant ULTR000445 from NCATS/NIH. Genome-wide genotyping
was funded by NIH grants RC2GM092618 from NIGMS/OD and
U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access
publication charges for this article was provided by a block
grant from Research Councils UK to the University of Cambridge
Cyprus women's health research (COHERE) initiative: determining the relative burden of women's health conditions and related co-morbidities in an Eastern Mediterranean population
Background: There is lack of population level data on prevalence and distribution of common benign women's health conditions such as endometriosis, uterine fibroids, polycystic ovary syndrome from the Eastern Mediterranean region despite their significant consequences on quality of life. In particular, there is complete absence of any health statistics from Northern Cyprus, which is an emerging region in Europe. The Cyprus Women's Health Research (COHERE) Initiative is the first large-scale cross-sectional study in the region, aiming to determine the relative burden of benign women's health conditions and related co-morbidities in women living in Northern Cyprus. Methods: The COHERE Initiative is a cross-sectional study aiming to recruit 8000 women aged 18 55 years and residing for at least the past 5 years in Northern Cyprus. The study is composed of two main steps: (1) Baseline recruitment, including (i) completion of a detailed health questionnaire, which is an expanded version of the World Endometriosis Research Foundation (WERF) Endometriosis Phenome Harmonisation Project (EPHect) standardised questionnaire, including questions on demographics, menstrual history, hormone use, pregnancy, pain (pelvic pain, bladder and bowel pain, migraine), medical history, family history of illnesses, medication use, life-style factors in relation to a wide range of reproductive and endocrine conditions, resource use (ii) measurement of weight, height, waist/hip circumference and blood pressure, (iii) collection of saliva samples for genotyping. (2) Gynaecology clinic follow up, including a pelvic ultrasound scan (USS). There is also a follow-up food frequency questionnaire (FFQ) targeted to all women taking part in the baseline recruitment with an aim to collect more detailed data on dietary habits. Discussion: The COHERE Initiative will generate prevalence rates for conditions, define the clinical profiles for women's health conditions, and estimate the economic burden of these conditions in Northern Cyprus. The results will also provide insights into the current status of health-care among women living in a currently under-investigated region. The genetic findings will inform future gene mapping studies for investigation of the heritable component of conditions in this population/region. Moreover, the results will be compared with other centres collecting data using EPHect tools globally and will help determine population differences and similarities in disease patterns and clinical profiles. The COHERE Initiative will serve as a resource to conduct hypothesis-driven follow-up studies investigating effect of the Mediterranean life-style' as well as genetic factors on common benign women's health conditions that maybe specific to Eastern Mediterranean populations
A polygenic and phenotypic risk prediction for polycystic ovary syndrome evaluated by phenomewide association studies
Context: As many as 75% of patients with polycystic ovary syndrome (PCOS) are estimated tobe unidentified in clinical practice. Objective: Utilizing polygenic risk prediction, we aim to identify the phenome-widecomorbidity patterns characteristic of PCOS to improve accurate diagnosis and preventivetreatment.Design, Patients, and Methods: Leveraging the electronic health records (EHRs) of 124 852individuals, we developed a PCOS risk prediction algorithm by combining polygenic risk scores(PRS) with PCOS component phenotypes into a polygenic and phenotypic risk score (PPRS). Weevaluated its predictive capability across different ancestries and perform a PRS-based phenomewide association study (PheWAS) to assess the phenomic expression of the heightened risk ofPCOS.Results: The integrated polygenic prediction improved the average performance (pseudo-R2)for PCOS detection by 0.228 (61.5-fold), 0.224 (58.8-fold), 0.211 (57.0-fold) over the null modelacross European, African, and multi-ancestry participants respectively. The subsequent PRSpowered PheWAS identified a high level of shared biology between PCOS and a range ofmetabolic and endocrine outcomes, especially with obesity and diabetes: "morbid obesity","type 2 diabetes", "hypercholesterolemia", "disorders of lipid metabolism", "hypertension",and "sleep apnea" reaching phenome-wide significance.Conclusions: Our study has expanded the methodological utility of PRS in patient stratificationand risk prediction, especially in a multifactorial condition like PCOS, across different geneticorigins. By utilizing the individual genome-phenome data available from the EHR, our approachalso demonstrates that polygenic prediction by PRS can provide valuable opportunities todiscover the pleiotropic phenomic network associated with PCOS pathogenesis.Abbreviations: AA, African ancestry; ANOVA, analysis of variance; BMI, body mass index; EA,European ancestry; EHR, electronic health records; eMERGE, electronic Medical Records andGenomics Network; GWAS, genome-wide association study; IBD, identity-by-descent; ICDCM, International Classification of Diseases, Clinical Modification; LD, linkage disequilibrium;MA, multi-ancestry; MAF, minor allele frequency; NIH, National Institutes of Health; PCA,principal component analysis; PheWAS, phenome-wide association study; PCOS, polycysticovary syndrome; PPRS, polygenic and phenotypic risk score; PRS, polygenic risk sc
Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology
Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p <1 x 10(-4)) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.Peer reviewe
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