Sage Journals: Discover world-class research

Abstract

Objective:

To identify novel susceptibility genes for age at natural menopause (ANM).

Methods:

Using transcription data generated in tissues from normal hypothalami (n = 73) and ovaries (n = 68) and high-density genotyping data provided by the Genotype-Tissue Expression (GTEx) database, we built 16 164 genetic models to predict gene expression across the transcriptome in these tissues. We used these models and summary statistics data from genome-wide association studies (GWAS) of ANM generated in 69 360 women of European ancestry to identify genes with their predicted expression related to ANM.

Results:

We found the predicted expression of 34 genes to be significantly associated with ANM at a Bonferroni-corrected threshold of P < 3.09 ×10⁻⁶. These include 4 genes located more than 1 Mb away from any previously GWAS-identified ANM-associated variants, 24 genes that reside in known GWAS-identified loci but have not been previously implicated, and 6 genes previously implicated as ANM-associated genes.

Conclusion:

Results from this transcriptome-wide association study, which integrated Expression quantitative trait loci (eQTL) data with summary statistics of GWAS of ANM, improves our understanding of the genetics and biology of female reproductive aging.

Keywords

transcriptome-wide association studies expression quantitative trait loci genome-wide association studies age at natural menopause

Get full access to this article

View all access options for this article.

References

Day

Ruth

Thompson

. Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair. Nat Genet. 2015;47(11):1294–1303.

Hinds

Price

. Menopause, hormone replacement and gynaecological cancers. Menopause Int. 2010;16(2):89–93.

Parker

Troisi

Wise

. Menarche, menopause, years of menstruation, and the incidence of osteoporosis: the influence of prenatal exposure to diethylstilbestrol. J Clin Endocrinol Metab. 2014;99(2):594–601.

Qiu

Chen

Wen

. Associations between age at menarche and menopause with cardiovascular disease, diabetes, and osteoporosis in Chinese women. J Clin Endocrinol Metab. 2013;98(4):1612–1621.

Velie

Nechuta

Osuch

. Lifetime reproductive and anthropometric risk factors for breast cancer in postmenopausal women. Breast Dis. 2005;24:17–35.

Vogel

. Epidemiology, genetics, and risk evaluation of postmenopausal women at risk of breast cancer. Menopause. 2008;15(4 suppl):782–789.

Kraft

Chen

. Genome-wide association studies identify loci associated with age at menarche and age at natural menopause. Nat Genet. 2009;41(6):724–728.

Stolk

Zhai

van Meurs

JBJ

. Loci at chromosomes 13, 19 and 20 influence age at natural menopause. Nat Genet. 2009;41(6):645–647.

Stolk

Perry

JRB

Chasman

. Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways. Nat Genet. 2012;44(3):260–268.

10.

Nicolae

Gamazon

Zhang

Duan

Dolan

Cox

. Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet. 2010;6(4):e1000888.

11.

Nica

Montgomery

Dimas

. Candidate causal regulatory effects by integration of expression QTLs with complex trait genetic associations. PLoS Genet. 2010;6(4):e1000895.

12.

Albert

Kruglyak

. The role of regulatory variation in complex traits and disease. Nat Rev Genet. 2015;16(4):197–212.

13.

Gamazon

Wheeler

Shah

. A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. 2015;47(9):1091–1098.

14.

Gusev

Shi

. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016;48(3):245–252.

15.

Zhu

Zhang

. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016;48(5):481–487.

16.

Pavlides

JMW

Zhu

Gratten

McRae

Wray

Yang

. Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits. Genome Med. 2016;8(1):84.

17.

Mancuso

Shi

Goddard

Kichaev

Gusev

Pasaniuc

. Integrating gene expression with summary association statistics to identify genes associated with 30 complex traits. Am J Hum Genet. 2017;100(3):473–487.

18.

Day

Thompson

Helgason

. Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk. Nat Genet. 2017;49(6):834–841.

19.

GTEx Consortium. Human genomics. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science. 2015;348(6235):648–660.

20.

McCarthy

Das

Kretzschmar

. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016;48(10):1279–1283.

21.

Howie

Donnelly

Marchini

. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 2009;5(6):e1000529.

22.

Delaneau

Marchini

Zagury

J-F

. A linear complexity phasing method for thousands of genomes. Nat Methods. 2011;9(2):179–181.

23.

DeLuca

Levin

Sivachenko

. RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinforma Oxf Engl. 2012;28(11):1530–1532.

24.

Stegle

Parts

Piipari

Winn

Durbin

. Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses. Nat Protoc. 2012;7(3):500–507.

25.

Guo

Lin

Rockowitz

Lachman

Zheng

. Characterization of human pseudogene-derived non-coding RNAs for functional potential. PloS One. 2014;9(4):e93972.

26.

Barbeira

Shah

Torres

. MetaXcan: summary statistics based gene-level association method infers accurate predixcan results. bioRxiv. 2016; https://doi.org/10.1101/045260

27.

Krämer

Green

Pollard

Tugendreich

. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinforma Oxf Engl. 2014;30:523–530.

28.

Yang

Ferreira

Morris

, Genetic Investigation of ANthropometric Traits (GIANT) Consortium; DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat Genet. 2012;44(4):369–375, S1–S3.

29.

Shiratori

Okumura

Nogami

. Assignment of the 49-kDa (PRIM1) and 58-kDa (PRIM2A and PRIM2B) subunit genes of the human DNA primase to chromosome bands 1q44 and 6p11.1-p12. Genomics. 1995;28(2):350–353.

30.

Hattori

Fujiwara

Maeda

Fujii

Ueda

. Epoxide hydrolase affects estrogen production in the human ovary. Endocrinology. 2000;141(9):3353–3365.

31.

Sang

Wang

. Quantitative methylation level of the EPHX1 promoter in peripheral blood DNA is associated with polycystic ovary syndrome. PloS One. 2014;9(2):e88013.

32.

Cerk

Schwarzenbacher

Adiprasito

. Current status of long non-coding RNAs in human breast cancer. Int J Mol Sci. 2016;17(9). pii: E1485.

33.

Evans

Feng

Chinnaiyan

. The bright side of dark matter: lncRNAs in cancer. J Clin Invest. 2016;126(8):2775–2782.

34.

Sudlow

Gallacher

Allen

. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 2015;12(3):e1001779.

35.

Chapman

Cree

Shelling

. The genetics of premature ovarian failure: current perspectives. Int J Womens Health. 2015;7:799–810.

36.

Rossetti

Ferrari

Bonomi

Persani

. Genetics of primary ovarian insufficiency. Clin Genet. 2017;91(2):183–198.

37.

Shelling

. Premature ovarian failure. Reprod Camb Engl. 2010;140(5):633–641.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.46 MB