Association between mitochondrial genetic variation and breast cancer risk: The Multiethnic Cohort
Authors:
Yuqing Li aff001; Elena E. Giorgi aff002; Kenneth B. Beckman aff003; Christian Caberto aff004; Remi Kazma aff005; Annette Lum-Jones aff004; Christopher A. Haiman aff006; Loïc Le Marchand aff004; Daniel O. Stram aff006; Richa Saxena aff007; Iona Cheng aff001
Authors place of work:
Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, California, United States of America
aff001; Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico
aff002; University of Minnesota Genomics Center, Minneapolis, Minnesota, United States of America
aff003; Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, Hawaii, United States of America
aff004; Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Switzerland
aff005; Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, United States of America
aff006; Center for Human Genetic Research, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
aff007; Program of Medical and Population Genetics, The Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
aff008
Published in the journal:
PLoS ONE 14(10)
Category:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0222284
Summary
Background
The mitochondrial genome encodes for thirty-seven proteins, among them thirteen are essential for the oxidative phosphorylation (OXPHOS) system. Inherited variation in mitochondrial genes may influence cancer development through changes in mitochondrial proteins, altering the OXPHOS process and promoting the production of reactive oxidative species.
Methods
To investigate the association between mitochondrial genetic variation and breast cancer risk, we tested 314 mitochondrial SNPs (mtSNPs), capturing four complexes of the mitochondrial OXPHOS pathway and mtSNP groupings for rRNA and tRNA, in 2,723 breast cancer cases and 3,260 controls from the Multiethnic Cohort Study.
Results
We examined the collective set of 314 mtSNPs as well as subsets of mtSNPs grouped by mitochondrial OXPHOS pathway, complexes, and genes, using the sequence kernel association test and adjusting for age, sex, and principal components of global ancestry. We also tested haplogroup associations using unconditional logistic regression and adjusting for the same covariates. Stratified analyses were conducted by self-reported maternal race/ethnicity. No significant mitochondrial OXPHOS pathway, gene, and haplogroup associations were observed in African Americans, Asian Americans, Latinos, and Native Hawaiians. In European Americans, a global test of all genetic variants of the mitochondrial genome identified an association with breast cancer risk (P = 0.017, q = 0.102). In mtSNP-subset analysis, the gene MT-CO2 (P = 0.001, q = 0.09) in Complex IV (cytochrome c oxidase) and MT-ND2 (P = 0.004, q = 0.19) in Complex I (NADH dehydrogenase (ubiquinone)) were significantly associated with breast cancer risk.
Conclusions
In summary, our findings suggest that collective mitochondrial genetic variation and particularly in the MT-CO2 and MT-ND2 may play a role in breast cancer risk among European Americans. Further replication is warranted in larger populations and future studies should evaluate the contribution of mitochondrial proteins encoded by both the nuclear and mitochondrial genomes to breast cancer risk.
Keywords:
Europe – Haplogroups – mitochondria – Mitochondrial DNA – breast cancer – Transfer RNA – African American people – Mitochondrial genetics
Background
Breast cancer is the most common cancer in women in the United States. In 2019, it has been estimated there will be 271,270 new cases of breast cancer in the United States [1]. Twin studies and familial studies suggested that heredity may account for ~49% of the risk of familial breast cancer [2–4]. To date, over 168 breast cancer risk loci have been identified by genome-wide association studies (GWAS) of breast cancer [5–22]; yet, inherited variants of germline mitochondrial DNA (mtDNA) have not been fully examined in relation to breast cancer susceptibility. To our knowledge, no study to date has comprehensively examined the relationship between the mitochondrial genome variants and breast cancer risk in multiple ethnic populations.
The mitochondrial genome is a small circular DNA molecule that spans 16.6 kb and has no intronic sequences [23]. This genome has become extremely specialized for the synthesis of proteins essential for the oxidative phosphorylation (OXPHOS) system and has retained only a small number of genes over the course of evolution [24]. Thirty-seven genes are encoded by the mitochondrial genome, comprising 13 essential polypeptides of the oxidation phosphorylation system and the RNA machinery necessary for their translation (2 ribosomal RNAs and 22 transfer RNAs)[24]. The remaining proteins of the mitochondrial electron transport chain and those needed for mtDNA maintenance are encoded by nuclear DNA and synthesized by cytoplasmic ribosomes [24].
The primary function of the mitochondrion is the production of the energy molecule, adenosine triphosphate (ATP), through the metabolic pathway of OXPHOS. In addition, the mitochondrion also serves as the major source of reactive oxygen species (ROS). ROS are involved in many cellular processes such as apoptosis, inflammation and oxidative stress. They are generally considered as toxic agents that contribute to aging, a wide variety of degenerative diseases, and cancer [25, 26]. Moreover, the mitochondrion itself is a sensitive target for the damaging effects of ROS. In particular, mtDNA is highly susceptible to oxidative damage due to its lack of protective histones and its close proximity to the electron transport chain, leading to instability of the mitochondrial genome in cancer cells [27–29]. In addition, less efficient DNA repair processes have been reported for mtDNA in comparison to nuclear DNA [30–32].
Variations in mtDNA have the potential to alter mitochondrial function and lead to increased oxidative stress and breast cancer risk [33–39]. Canter et al. tested the association between mtDNA G10398A and breast cancer risk firstly in 48 African American breast cancer cases and 54 African American controls followed by a validation study of 654 breast cancer cases and 605 controls [33], and reported an association in African-Americans (OR = 1.60, p value = 0.013), yet no association in Whites (OR = 1.03, p value = 0.81). Setiawan et al. found no association with mtDNA, G10398A and breast cancer risk [40] in a study of 1,456 African American breast cancer cases and 978 African American controls. Similarly, no association with mtDNA G10398A and breast cancer risk was found in a study of 716 cases and 724 controls in a South Indian population [35]. Recently, Blein et al. conducted a large scale study of 11,421 breast cancer affected and 10,793 unaffected BRCA1/2 mutation carriers of European ancestry, and identified an inverse association between mtDNA haplogroup T1a1 and breast cancer risk (Hazard Ratio = 0.62, 95% Confidence Interval = 0.40–0.95; P = 0.03) [37]. Other small studies have reported other candidate polymorphisms (G9055A, T16519 or G6267A) to be associated with breast cancer risk among European ancestry women [41, 42]. These inconsistent findings may be due to differences in study design, study populations, and small sample sizes with limited statistical power.
To investigate the association between mitochondrial genetic variation and breast cancer risk across multiple racial/ethnic groups, we tested 314 mtSNPs among 5,983 subjects (2,723 breast cancer cases and 3,260 controls) in the Multiethnic Cohort Study (MEC).
Methods
Study subjects
Our study included 2,723 incident breast cancer cases and 3,260 controls nested within the MEC, a large population-based cohort of more than 215,000 subjects comprised of African Americans, European Americans, Japanese Americans, Latinos, and Native Hawaiians, who were recruited from 1993 through 1996 at the ages of 45 and 75 years [43]. Blood samples were collected from incident breast and colorectal cancer cases after their diagnosis, as well as a random sample of cohort members to serve as controls from 1996 through 2001, and prospectively from all willing surviving participants from 2002 through 2007. Incident breast cancer cases were identified through cohort linkage to population-based cancer Surveillance, Epidemiology and End Results (SEER) registries in California and Hawaii up to December 9, 2010. Control subjects were women selected to not have breast cancer before cohort entry or during follow-up as of December 9, 2010 and served as matched controls on age (5-year age groups) and race/ethnicity for our nested breast and colorectal cancer studies. This study was approved by the institutional review board at the University of Hawaii and University of Southern California. Written informed consent was obtained from all subjects.
mtSNPs genotyping
Mitochondrial SNPs were genotyped using the Sequenom platform (n = 186 mtSNPs) [44] and the Illumina Exome array [45] (n = 240 mtSNPs). The 2,723 cases and 3,260 controls were shared between the two genotyping platforms with an average call rate of 99.83%. Forty mtSNPs were common in both genotyping platforms with a concordance rate of 99.3%. Of the 386 unique mtSNPs across the two genotyping platforms, we excluded 72 mtSNPs with MAF<0.1% among the overall sample, resulting in 314 mtSNPs that were distributed across 13 mtDNA genes, comprising four complexes of the OXPHOS pathway, and the tRNA and rRNA subunits (19 mtSNPs per kb).
Statistical analysis
For the mitochondrial genome, pathway, complex, gene-based analysis, we used the sequence kernel association test (SKAT) [46, 47]. The SKAT_commonrare test is an omnibus procedure allowing for both rare and common variants to contribute to the overall test statistic. For this test, the minor allele frequency of threshold for rare variants was determined by sample size (T=12n) [47] (0.1%< MAF<1% for African, Asian, European, Latino ancestry groups; 1%<MAF<5% for Native Hawaiians). All analyses were adjusted for age, self-reported maternal race/ethnicity, and the first five principal components of genetic ancestry. The principal components of genetic ancestry were estimated from a panel of 128 ancestry informative markers [48, 49]. For single mtSNP and haplogroup analyses, we conducted unconditional logistic regression, adjusting for the same covariates listed above. Haplogroups were estimated using the HaploGrep software (http://www.haplogrep.uibk.ac.at) and based on Phylotree build 16 [50, 51]. Additional adjustment for family history of breast cancer, age at menarche, age at first birth, age at menopause, parity, hormone replacement therapy (HRT) use, body mass index (BMI), alcohol, and smoking did not notably alter the results. Thus, these covariates were not included in our final multivariate models. Stratified analyses were conducted by self-reported maternal race/ethnicity. All statistical tests presented are two-sided. A false discovery rate (FDR) was used to account for multiple hypothesis testing for the mitochondrial genome, OXPHOS pathway, complexes, genes, and haplogroup for the five racial/ethnic groups and overall. A false discovery rate q value [52] of 0.20 was used as a threshold to determine statistical significance, which is equivalent to a nominal p value of 6.7x10-4 (0.2/300) for ~300 mtSNPs tested and p-value = 0.01 (0.2/20) for the ~20 mitochondrial gene-based tests.
Results
Study characteristics of the 5,983 study subjects (2,723 breast cancer cases; 3,260 controls) are presented in Table 1. The distribution of maternal race/ethnicity was 23.3% African Americans, 28.7% Asian Americans, 25.5% European Americans, 16.4% Latinos and 6.1% Native Hawaiians. Breast cancer cases were of younger age at menarche, older age at menopause, had fewer children, higher BMI, had higher use of hormone replacement therapy (HRT), more likely to have a family history of breast cancer, consume alcohol, and have a history of diabetes than controls. Approximately 72.2% of breast cancer cases had localized disease and 72.1% were hormone receptor positive. S1 Table shows the distribution of study characteristics by maternal race/ethnicity.
Mitochondrial genome, pathway, and gene analysis
No statistically significant associations were observed with the mitochondrial genomes, pathways, or genes in all groups combined and among African Americans, Asian Americans, Latinos, and Native Hawaiians (Table 2). Yet, in European Americans, a global test of the mitochondrial genome (collective set of 261 mtSNPs with MAF >0.1%) revealed an association with breast cancer risk (P = 0.017, q = 0.102; Table 2). In addition, two mtDNA genes, NADH dehydrogenase 2 (MT-ND2; P = 0.004, q = 0.19) and cytochrome c oxidase II (MT-CO2; P = 0.001, q = 0.095) were associated with breast cancer risk in European Americans (Table 2).
MtSNP and haplogroup associations
Overall among all groups combined, 11 of 314 mtSNPs were associated with breast cancer risk at P<0.05 (S2 Table) with the most significant association seen with tRNA mtSNP (mt15904; P = 0.005) that did not reach our FDR criterion of statistical significance. In maternal race/ethnicity stratified analyses of mtSNPs (MAF>0.01), 5 of 280 mtSNPs, 4 of 189 mtSNPs, 13 of 249 mtSNPs, and 7 of 240 mtSNPs were associated with breast cancer risk at P<0.05 in African Americans, Asian Americans, European Americans, and Latinos, respectively and did not reach our statistical significance threshold (S2 Table and Fig 1). No mtSNP associations were observed in Native Hawaiians. Haplogroup associations and frequencies by case/control status for each maternal racial/ethnic group are presented in S3 Table. No haplogroup associations were seen across the five racial/ethnic groups.
Discussion
In this study, we comprehensively examined the association between the mitochondrial genetic variation and breast cancer risk in five racial/ethnic groups. To our knowledge, this is the first study to examine the collective mitochondrial genome, pathways, genes, and mtSNPs for their associations with breast cancer risk in a multiethnic population. No mitochondrial genome associations were observed in African Americans, Asian Americans, Latinos, and Native Hawaiians. Yet, an association between mitochondrial genetic variation and breast cancer risk was observed among European Americans.
In European Americans, the most significant association was seen with the MT-CO2 gene that is part of the respiratory Complex IV (cytochrome c oxidase). In vitro studies have reported over expression of MT-CO2 in human breast cancer epithelial cells and reduced breast tumor growth with treatment of a MT-CO2 inhibitor [53, 54]. The other significant association was observed with the MT-ND2 gene, a member of the OXPHOS pathway that encodes for the subunit of NADH. It is reasonable to hypothesize that mtDNA coding variants in MT-CO2 and MT-ND2 genes may have cis-acting effects on the expression of these genes that may be distinct to European ancestry populations as a recent study reported specific SNP-gene expression patterns between African and Caucasian populations [55]. In addition, nuclear DNA encoded transcription factors have been shown to bind to coding regions in mtDNA to regulate gene expression [56–58].
In a large study of BRCA1/2 mutation carriers in the CIMBA consortium (11,421 cases/ 10,793 controls), haplogroup T1a1 was inversely associated with breast cancer risk (Hazard Ratio = 0.62; P = 0.03) among BRCA1 carriers of European ancestry [37]. Our study did not observe an association between haplogroup T1a1 and breast cancer risk, which may be attributed to differences in our population-based study population in comparison to BRCA1/2 carriers and differences in study power. A small study of European women (164 breast cancer cases/ 164 controls) reported haplogroup H to be associated with breast cancer risk (OR = 2.0; 95% CI: 1.1–3.5) [36]. In our study, haplogroup HV was not statistically significantly associated with breast cancer risk in European Americans (OR = 1.59, 95%CI: 0.99–2.57, P = 0.059) (S3 Table).
Two small case-control studies reported mtDNA G13708A to be associated with breast cancer risk in African American and South Indian women, but three other studies [34, 35, 40] failed to confirm an association. We found no association with this specific polymorphism and the MT-ND5 gene.
Our study has several strengths. Given the wide spectrum of rare, low-frequency, and common genetic variants in the mitochondrial genome, the use of the SKAT common/rare approach to collectively test multiple risk alleles has improved statistical power to detect modest effects than single SNP tests and overcomes the limitation of previous methods that upweight rare variants [47, 59]. Using this approach, we were able to capture the role of multiple mtDNA genes involved in breast cancer risk. In addition, we expect bias due to heteroplasmy to be unlikely, as prior work has reported heteroplasmy in blood DNA to be quite small [60]. We do recognize the limitation of the modest sample size to detect weak genetic effects for certain subgroups such as Native Hawaiians.
Conclusion
In summary, our findings suggest that collectively multiple mtDNA variants may play a role in breast cancer risk in European Americans. The findings of association between the mitochondrial OXPHOS pathway and multiple mitochondrial complexes and genes warrant replication in other European population. Further studies in larger populations should evaluate both the mitochondrial genome and nuclear encoded mitochondrial genomes to fully examine their contribution to breast cancer risk. A recent study examined the association between nuclear genetic variation and mitochondrial transcript abundance based on genotyping data and RNA sequencing data for 36 tissues/cell types, and found 64 nuclear loci associated with expression level of 14 genes encoded by the mitochondrial genome that included missense variants of genes involved in mitochondrial function [61].
Supporting information
S1 Table [xlsx]
Study characteristics of 2,723 breast cancer cases and 3,260 controls by maternal race/ethnicity in the MEC.
S2 Table [xlsx]
314 mtSNPs tested in 2,723 breast cancer cases and 3,260 controls in the MEC.
S3 Table [xlsx]
Association between mitochondrial haplogroups and breast cancer risk by maternal race/ethnicity in the MEC.
Zdroje
1. American Cancer Society. Cancer Facts & Figures 2015. Atlanta: American Cancer Society. 2019.
2. Lichtenstein P, Holm NV, Verkasalo PK, Iliadou A, Kaprio J, Koskenvuo M, et al. Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark, and Finland. N Engl J Med. 2000;343(2):78–85. Epub 2000/07/13. doi: 10.1056/NEJM200007133430201 10891514.
3. Fachal L, Dunning AM. From candidate gene studies to GWAS and post-GWAS analyses in breast cancer. Curr Opin Genet Dev. 2015;30:32–41. Epub 2015/03/03. S0959-437X(15)00005-2 [pii] doi: 10.1016/j.gde.2015.01.004 25727315.
4. Swerdlow AJ, De Stavola BL, Swanwick MA, Maconochie NE. Risks of breast and testicular cancers in young adult twins in England and Wales: evidence on prenatal and genetic aetiology. Lancet. 1997;350(9093):1723–8. Epub 1997/12/31. S0140673697055268 [pii]. doi: 10.1016/s0140-6736(97)05526-8 9413462.
5. Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, et al. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 2014;42(Database issue):D1001–6. Epub 2013/12/10. gkt1229 [pii] doi: 10.1093/nar/gkt1229 24316577; PubMed Central PMCID: PMC3965119.
6. Easton DF, Pooley KA, Dunning AM, Pharoah PD, Thompson D, Ballinger DG, et al. Genome-wide association study identifies novel breast cancer susceptibility loci. Nature. 2007;447(7148):1087–93. Epub 2007/05/29. nature05887 [pii] doi: 10.1038/nature05887 17529967; PubMed Central PMCID: PMC2714974.
7. Hunter DJ, Kraft P, Jacobs KB, Cox DG, Yeager M, Hankinson SE, et al. A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat Genet. 2007;39(7):870–4. Epub 2007/05/29. ng2075 [pii] doi: 10.1038/ng2075 17529973; PubMed Central PMCID: PMC3493132.
8. Stacey SN, Manolescu A, Sulem P, Rafnar T, Gudmundsson J, Gudjonsson SA, et al. Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet. 2007;39(7):865–9. Epub 2007/05/29. ng2064 [pii] doi: 10.1038/ng2064 17529974.
9. Gold B, Kirchhoff T, Stefanov S, Lautenberger J, Viale A, Garber J, et al. Genome-wide association study provides evidence for a breast cancer risk locus at 6q22.33. Proc Natl Acad Sci U S A. 2008;105(11):4340–5. Epub 2008/03/11. 0800441105 [pii] doi: 10.1073/pnas.0800441105 18326623; PubMed Central PMCID: PMC2393811.
10. Turnbull C, Ahmed S, Morrison J, Pernet D, Renwick A, Maranian M, et al. Genome-wide association study identifies five new breast cancer susceptibility loci. Nat Genet. 2010;42(6):504–7. Epub 2010/05/11. ng.586 [pii] doi: 10.1038/ng.586 20453838; PubMed Central PMCID: PMC3632836.
11. Cai Q, Long J, Lu W, Qu S, Wen W, Kang D, et al. Genome-wide association study identifies breast cancer risk variant at 10q21.2: results from the Asia Breast Cancer Consortium. Hum Mol Genet. 2011;20(24):4991–9. Epub 2011/09/13. ddr405 [pii] doi: 10.1093/hmg/ddr405 21908515; PubMed Central PMCID: PMC3221542.
12. Fletcher O, Johnson N, Orr N, Hosking FJ, Gibson LJ, Walker K, et al. Novel breast cancer susceptibility locus at 9q31.2: results of a genome-wide association study. J Natl Cancer Inst. 2011;103(5):425–35. Epub 2011/01/26. djq563 [pii] doi: 10.1093/jnci/djq563 21263130.
13. Kim HC, Lee JY, Sung H, Choi JY, Park SK, Lee KM, et al. A genome-wide association study identifies a breast cancer risk variant in ERBB4 at 2q34: results from the Seoul Breast Cancer Study. Breast Cancer Res. 2012;14(2):R56. Epub 2012/03/29. bcr3158 [pii] doi: 10.1186/bcr3158 22452962; PubMed Central PMCID: PMC3446390.
14. Long J, Cai Q, Sung H, Shi J, Zhang B, Choi JY, et al. Genome-wide association study in east Asians identifies novel susceptibility loci for breast cancer. PLoS Genet. 2012;8(2):e1002532. Epub 2012/03/03. doi: 10.1371/journal.pgen.1002532 PGENETICS-D-11-01537 [pii]. 22383897; PubMed Central PMCID: PMC3285588.
15. Siddiq A, Couch FJ, Chen GK, Lindstrom S, Eccles D, Millikan RC, et al. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11. Hum Mol Genet. 2012;21(24):5373–84. Epub 2012/09/15. dds381 [pii] doi: 10.1093/hmg/dds381 22976474; PubMed Central PMCID: PMC3510753.
16. Garcia-Closas M, Couch FJ, Lindstrom S, Michailidou K, Schmidt MK, Brook MN, et al. Genome-wide association studies identify four ER negative-specific breast cancer risk loci. Nat Genet. 2013;45(4):392–8, 8e1-2. Epub 2013/03/29. ng.2561 [pii] doi: 10.1038/ng.2561 23535733; PubMed Central PMCID: PMC3771695.
17. Low SK, Takahashi A, Ashikawa K, Inazawa J, Miki Y, Kubo M, et al. Genome-wide association study of breast cancer in the Japanese population. PLoS One. 2013;8(10):e76463. Epub 2013/10/22. doi: 10.1371/journal.pone.0076463 PONE-D-13-29227 [pii]. 24143190; PubMed Central PMCID: PMC3797071.
18. Michailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne RL, et al. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet. 2013;45(4):353–61, 61e1-2. Epub 2013/03/29. ng.2563 [pii] doi: 10.1038/ng.2563 23535729; PubMed Central PMCID: PMC3771688.
19. Ahsan H, Halpern J, Kibriya MG, Pierce BL, Tong L, Gamazon E, et al. A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age. Cancer Epidemiol Biomarkers Prev. 2014;23(4):658–69. Epub 2014/02/05. 1055-9965.EPI-13-0340 [pii] doi: 10.1158/1055-9965.EPI-13-0340 24493630; PubMed Central PMCID: PMC3990360.
20. Cai Q, Zhang B, Sung H, Low SK, Kweon SS, Lu W, et al. Genome-wide association analysis in East Asians identifies breast cancer susceptibility loci at 1q32.1, 5q14.3 and 15q26.1. Nat Genet. 2014;46(8):886–90. Epub 2014/07/21. ng.3041 [pii] doi: 10.1038/ng.3041 25038754; PubMed Central PMCID: PMC4127632.
21. Fejerman L, Ahmadiyeh N, Hu D, Huntsman S, Beckman KB, Caswell JL, et al. Genome-wide association study of breast cancer in Latinas identifies novel protective variants on 6q25. Nat Commun. 2014;5:5260. Epub 2014/10/21. ncomms6260 [pii] doi: 10.1038/ncomms6260 25327703; PubMed Central PMCID: PMC4204111.
22. Michailidou K, Lindstrom S, Dennis J, Beesley J, Hui S, Kar S, et al. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551(7678):92–4. doi: 10.1038/nature24284 29059683; PubMed Central PMCID: PMC5798588.
23. Anderson L. Identification of mitochondrial proteins and some of their precursors in two-dimensional electrophoretic maps of human cells. Proc Natl Acad Sci U S A. 1981;78(4):2407–11. Epub 1981/04/01. doi: 10.1073/pnas.78.4.2407 6941300; PubMed Central PMCID: PMC319355.
24. Taylor RW, Turnbull DM. Mitochondrial DNA mutations in human disease. Nat Rev Genet. 2005;6(5):389–402. doi: 10.1038/nrg1606 15861210.
25. Hervouet E, Simonnet H, Godinot C. Mitochondria and reactive oxygen species in renal cancer. Biochimie. 2007;89(9):1080–8. doi: 10.1016/j.biochi.2007.03.010 17466430.
26. Kujoth GC, Prolla TA. Evolving insight into the role of mitochondrial DNA mutations in aging. Exp Gerontol. 2008;43(1):20–3. doi: 10.1016/j.exger.2007.09.010 18054193.
27. Jackson AL, Loeb LA. The contribution of endogenous sources of DNA damage to the multiple mutations in cancer. Mutat Res. 2001;477(1–2):7–21. doi: 10.1016/s0027-5107(01)00091-4 11376682.
28. Lee HC, Yin PH, Lin JC, Wu CC, Chen CY, Wu CW, et al. Mitochondrial genome instability and mtDNA depletion in human cancers. Ann N Y Acad Sci. 2005;1042:109–22. doi: 10.1196/annals.1338.011 15965052.
29. Marcelino LA, Thilly WG. Mitochondrial mutagenesis in human cells and tissues. Mutat Res. 1999;434(3):177–203. doi: 10.1016/s0921-8777(99)00028-2 10486591.
30. Beal MF. Mitochondria, free radicals, and neurodegeneration. Curr Opin Neurobiol. 1996;6(5):661–6. doi: 10.1016/s0959-4388(96)80100-0 8937831.
31. Croteau DL, Bohr VA. Repair of oxidative damage to nuclear and mitochondrial DNA in mammalian cells. J Biol Chem. 1997;272(41):25409–12. doi: 10.1074/jbc.272.41.25409 9325246.
32. Lightowlers RN, Chinnery PF, Turnbull DM, Howell N. Mammalian mitochondrial genetics: heredity, heteroplasmy and disease. Trends Genet. 1997;13(11):450–5. doi: 10.1016/s0168-9525(97)01266-3 9385842.
33. Canter JA, Kallianpur AR, Parl FF, Millikan RC. Mitochondrial DNA G10398A polymorphism and invasive breast cancer in African-American women. Cancer Res. 2005;65(17):8028–33. Epub 2005/09/06. 65/17/8028 [pii] doi: 10.1158/0008-5472.CAN-05-1428 16140977.
34. Mosquera-Miguel A, Alvarez-Iglesias V, Carracedo A, Salas A, Vega A, Milne R, et al. Is mitochondrial DNA variation associated with sporadic breast cancer risk? Cancer Res. 2008;68(2):623–5; author reply 4. Epub 2008/01/18. 68/2/623 [pii] doi: 10.1158/0008-5472.CAN-07-2385 18199560.
35. Francis A, Pooja S, Rajender S, Govindaraj P, Tipirisetti NR, Surekha D, et al. A mitochondrial DNA variant 10398G>A in breast cancer among South Indians: an original study with meta-analysis. Mitochondrion. 2013;13(6):559–65. Epub 2013/09/03. S1567-7249(13)00237-7 [pii] doi: 10.1016/j.mito.2013.08.004 23993954.
36. Bonilla C, Bertoni B, Hidalgo PC, Artagaveytia N, Ackermann E, Barreto I, et al. Breast cancer risk and genetic ancestry: a case-control study in Uruguay. BMC Womens Health. 2015;15:11. Epub 2015/03/19. doi: 10.1186/s12905-015-0171-8 25783644; PubMed Central PMCID: PMC4341228.
37. Blein S, Bardel C, Danjean V, McGuffog L, Healey S, Barrowdale D, et al. An original phylogenetic approach identified mitochondrial haplogroup T1a1 as inversely associated with breast cancer risk in BRCA2 mutation carriers. Breast Cancer Res. 2015;17:61. Epub 2015/05/01. doi: 10.1186/s13058-015-0567-2 [pii]. 25925750; PubMed Central PMCID: PMC4478717.
38. Covarrubias D, Bai RK, Wong LJ, Leal SM. Mitochondrial DNA variant interactions modify breast cancer risk. J Hum Genet. 2008;53(10):924–8. Epub 2008/08/19. doi: 10.1007/s10038-008-0331-x 18709563; PubMed Central PMCID: PMC2767522.
39. Pezzotti A, Kraft P, Hankinson SE, Hunter DJ, Buring J, Cox DG. The mitochondrial A10398G polymorphism, interaction with alcohol consumption, and breast cancer risk. PLoS One. 2009;4(4):e5356. Epub 2009/04/25. doi: 10.1371/journal.pone.0005356 19390621; PubMed Central PMCID: PMC2668794.
40. Setiawan VW, Chu LH, John EM, Ding YC, Ingles SA, Bernstein L, et al. Mitochondrial DNA G10398A variant is not associated with breast cancer in African-American women. Cancer Genet Cytogenet. 2008;181(1):16–9. Epub 2008/02/12. S0165-4608(07)00709-1 [pii] doi: 10.1016/j.cancergencyto.2007.10.019 18262047; PubMed Central PMCID: PMC3225405.
41. Bai RK, Leal SM, Covarrubias D, Liu A, Wong LJ. Mitochondrial genetic background modifies breast cancer risk. Cancer Res. 2007;67(10):4687–94. Epub 2007/05/19. 67/10/4687 [pii] doi: 10.1158/0008-5472.CAN-06-3554 17510395.
42. Gallardo ME, Moreno-Loshuertos R, Lopez C, Casqueiro M, Silva J, Bonilla F, et al. m.6267G>A: a recurrent mutation in the human mitochondrial DNA that reduces cytochrome c oxidase activity and is associated with tumors. Hum Mutat. 2006;27(6):575–82. doi: 10.1002/humu.20338 16671096.
43. Kolonel LN, Henderson BE, Hankin JH, Nomura AM, Wilkens LR, Pike MC, et al. A multiethnic cohort in Hawaii and Los Angeles: baseline characteristics. Am J Epidemiol. 2000;151(4):346–57. doi: 10.1093/oxfordjournals.aje.a010213 10695593.
44. Li Y, Beckman KB, Caberto C, Kazma R, Lum-Jones A, Haiman CA, et al. Association of Genes, Pathways, and Haplogroups of the Mitochondrial Genome with the Risk of Colorectal Cancer: The Multiethnic Cohort. PLoS One. 2015;10(9):e0136796. Epub 2015/09/05. doi: 10.1371/journal.pone.0136796 PONE-D-15-26620 [pii]. 26340450; PubMed Central PMCID: PMC4560485.
45. Cheng I, Chen GK, Nakagawa H, He J, Wan P, Laurie CC, et al. Evaluating genetic risk for prostate cancer among Japanese and Latinos. Cancer Epidemiol Biomarkers Prev. 2012;21(11):2048–58. doi: 10.1158/1055-9965.EPI-12-0598 22923026; PubMed Central PMCID: PMC3494732.
46. Wu MC, Lee S, Cai T, Li Y, Boehnke M, Lin X. Rare-variant association testing for sequencing data with the sequence kernel association test. Am J Hum Genet. 2011;89(1):82–93. Epub 2011/07/09. S0002-9297(11)00222-9 [pii] doi: 10.1016/j.ajhg.2011.05.029 21737059; PubMed Central PMCID: PMC3135811.
47. Ionita-Laza I, Lee S, Makarov V, Buxbaum JD, Lin X. Sequence kernel association tests for the combined effect of rare and common variants. Am J Hum Genet. 2013;92(6):841–53. Epub 2013/05/21. S0002-9297(13)00176-6 [pii] doi: 10.1016/j.ajhg.2013.04.015 23684009; PubMed Central PMCID: PMC3675243.
48. Kosoy R, Nassir R, Tian C, White PA, Butler LM, Silva G, et al. Ancestry informative marker sets for determining continental origin and admixture proportions in common populations in America. Human Mutation. 2009;30(1):69–78. doi: 10.1002/humu.20822 18683858
49. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38(8):904–9. Epub 2006/07/25. ng1847 [pii] doi: 10.1038/ng1847 16862161.
50. van Oven M, Kayser M. Updated comprehensive phylogenetic tree of global human mitochondrial DNA variation. Hum Mutat. 2009;30(2):E386–94. Epub 2008/10/15. doi: 10.1002/humu.20921 18853457.
51. Kloss-Brandstatter A, Pacher D, Schonherr S, Weissensteiner H, Binna R, Specht G, et al. HaploGrep: a fast and reliable algorithm for automatic classification of mitochondrial DNA haplogroups. Hum Mutat. 2011;32(1):25–32. Epub 2010/10/21. doi: 10.1002/humu.21382 20960467.
52. Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci U S A. 2003;100(16):9440–5. Epub 2003/07/29. doi: 10.1073/pnas.1530509100 1530509100 [pii]. 12883005; PubMed Central PMCID: PMC170937.
53. Singh R, Parveen M, Basgen JM, Fazel S, Meshesha MF, Thames EC, et al. Increased Expression of Beige/Brown Adipose Markers from Host and Breast Cancer Cells Influence Xenograft Formation in Mice. Mol Cancer Res. 2016;14(1):78–92. doi: 10.1158/1541-7786.MCR-15-0151 26464213; PubMed Central PMCID: PMC4749269.
54. Lamb R, Ozsvari B, Bonuccelli G, Smith DL, Pestell RG, Martinez-Outschoorn UE, et al. Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells. Oncotarget. 2015;6(26):21892–905. doi: 10.18632/oncotarget.5260 26323205; PubMed Central PMCID: PMC4673134.
55. Cohen T, Levin L, Mishmar D. Ancient Out-of-Africa Mitochondrial DNA Variants Associate with Distinct Mitochondrial Gene Expression Patterns. PLoS Genet. 2016;12(11):e1006407. doi: 10.1371/journal.pgen.1006407 27812116; PubMed Central PMCID: PMC5094714.
56. Leigh-Brown S, Enriquez JA, Odom DT. Nuclear transcription factors in mammalian mitochondria. Genome Biol. 2010;11(7):215. doi: 10.1186/gb-2010-11-7-215 20670382; PubMed Central PMCID: PMC2926779.
57. She H, Yang Q, Shepherd K, Smith Y, Miller G, Testa C, et al. Direct regulation of complex I by mitochondrial MEF2D is disrupted in a mouse model of Parkinson disease and in human patients. J Clin Invest. 2011;121(3):930–40. doi: 10.1172/JCI43871 21393861; PubMed Central PMCID: PMC3049386.
58. Grober OM, Mutarelli M, Giurato G, Ravo M, Cicatiello L, De Filippo MR, et al. Global analysis of estrogen receptor beta binding to breast cancer cell genome reveals an extensive interplay with estrogen receptor alpha for target gene regulation. BMC Genomics. 2011;12:36. doi: 10.1186/1471-2164-12-36 21235772; PubMed Central PMCID: PMC3025958.
59. Wu MC, Kraft P, Epstein MP, Taylor DM, Chanock SJ, Hunter DJ, et al. Powerful SNP-set analysis for case-control genome-wide association studies. Am J Hum Genet. 2010;86(6):929–42. Epub 2010/06/22. S0002-9297(10)00248-X [pii] doi: 10.1016/j.ajhg.2010.05.002 20560208; PubMed Central PMCID: PMC3032061.
60. Saxena R, de Bakker PI, Singer K, Mootha V, Burtt N, Hirschhorn JN, et al. Comprehensive association testing of common mitochondrial DNA variation in metabolic disease. Am J Hum Genet. 2006;79(1):54–61. doi: 10.1086/504926 16773565; PubMed Central PMCID: PMC1474138.
61. Ali AT, Boehme L, Carbajosa G, Seitan VC, Small KS, Hodgkinson A. Nuclear genetic regulation of the human mitochondrial transcriptome. Elife. 2019;8. doi: 10.7554/eLife.41927 30775970; PubMed Central PMCID: PMC6420317.
Článek vyšel v časopise
PLOS One
2019 Číslo 10
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Je libo čepici místo mozkového implantátu?
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Pomůže v budoucnu s triáží na pohotovostech umělá inteligence?
- AI může chirurgům poskytnout cenná data i zpětnou vazbu v reálném čase
Nejčtenější v tomto čísle
- Correction: Low dose naltrexone: Effects on medication in rheumatoid and seropositive arthritis. A nationwide register-based controlled quasi-experimental before-after study
- Combining CDK4/6 inhibitors ribociclib and palbociclib with cytotoxic agents does not enhance cytotoxicity
- Experimentally validated simulation of coronary stents considering different dogboning ratios and asymmetric stent positioning
- Risk factors associated with IgA vasculitis with nephritis (Henoch–Schönlein purpura nephritis) progressing to unfavorable outcomes: A meta-analysis
