Examining the Effect of Genes on Depression as Mediated by Smoking and Modified by Sex
Abstract
:1. Introduction
2. Materials and Methods
2.1. Primary Population: UK Biobank
2.2. Replication Population: COPDGene
2.3. Statistical Analyses
3. Results
3.1. Characteristics of Participants
3.2. Mediation Analysis
3.3. Sex-Stratified and Sex-Moderated Mediation Analyses
4. Discussion
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- World Health Organization. Depression. 2021. Available online: https://www.who.int/news-room/fact-sheets/detail/depression (accessed on 13 November 2023).
- Sullivan, P.F.; Neale, M.C.; Kendler, K.S. Genetic epidemiology of major depression: Review and meta-analysis. Am. J. Psychiatry 2000, 157, 1552–1562. [Google Scholar] [CrossRef]
- Kendler, K.S.; Gatz, M.; Gardner, C.O.; Pedersen, N.L. A Swedish national twin study of lifetime major depression. Am. J. Psychiatry 2006, 163, 109–114. [Google Scholar] [CrossRef] [PubMed]
- Fluharty, M.; Taylor, A.E.; Grabski, M.; Munafò, M.R. The Association of Cigarette Smoking with Depression and Anxiety: A Systematic Review. Nicotine Tob. Res. 2017, 19, 3–13. [Google Scholar] [CrossRef] [PubMed]
- Taylor, A.E.; Fluharty, M.E.; Bjørngaard, J.H.; Gabrielsen, M.E.; Skorpen, F.; Marioni, R.E.; Campbell, A.; Engmann, J.; Mirza, S.S.; Loukola, A.; et al. Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis: The CARTA consortium. BMJ Open 2014, 4, e006141. [Google Scholar] [CrossRef] [PubMed]
- Salk, R.H.; Hyde, J.S.; Abramson, L.Y. Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychol. Bull. 2017, 143, 783–822. [Google Scholar] [CrossRef] [PubMed]
- Wang, S.; Ungvari, G.S.; Forester, B.P.; Chiu, H.F.; Wu, Y.; Kou, C.; Fu, Y.; Qi, Y.; Liu, Y.; Tao, Y.; et al. Gender differences in general mental health, smoking, drinking and chronic diseases in older adults in Jilin province, China. Psychiatry Res. 2017, 251, 58–62. [Google Scholar] [CrossRef]
- Sullivan, P.F.; de Geus, E.J.C.; Willemsen, G.; James, M.R.; Smit, J.H.; Zandbelt, T.; Arolt, V.; Baune, B.T.; Blackwood, D.; Cichon, S.; et al. Genome-wide association for major depressive disorder: A possible role for the presynaptic protein piccolo. Mol. Psychiatry 2009, 14, 359–375. [Google Scholar] [CrossRef] [PubMed]
- Noh, K.; Lee, H.; Choi, T.-Y.; Joo, Y.; Kim, S.-J.; Kim, H.; Kim, J.Y.; Jahng, J.W.; Lee, S.; Choi, S.-Y.; et al. Negr1 controls adult hippocampal neurogenesis and affective behaviors. Mol. Psychiatry 2019, 24, 1189–1205. [Google Scholar] [CrossRef]
- Wray, N.R.; Ripke, S.; Mattheisen, M.; Trzaskowski, M.; Byrne, E.M.; Abdellaoui, A.; Adams, M.J.; Agerbo, E.; Air, T.M.; Andlauer, T.M.F.; et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat. Genet. 2018, 50, 668–681. [Google Scholar] [CrossRef]
- Kendall, K.M.; Van Assche, E.; Andlauer, T.F.M.; Choi, K.W.; Luykx, J.J.; Schulte, E.C.; Lu, Y. The genetic basis of major depression. Psychol. Med. 2021, 51, 2217–2230. [Google Scholar] [CrossRef]
- Howard, D.M.; Adams, M.J.; Clarke, T.-K.; Hafferty, J.D.; Gibson, J.; Shirali, M.; Coleman, J.R.I.; Hagenaars, S.P.; Ward, J.; Wigmore, E.M.; et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat. Neurosci. 2019, 22, 343–352. [Google Scholar] [CrossRef]
- Hall, L.S.; Adams, M.J.; Arnau-Soler, A.; Clarke, T.-K.; Howard, D.M.; Zeng, Y.; Davies, G.; Hagenaars, S.P.; Fernandez-Pujals, A.M.; Gibson, J.; et al. Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank. Transl. Psychiatry 2018, 8, 9. [Google Scholar] [CrossRef]
- Bulik-Sullivan, B.; Finucane, H.K.; Anttila, V.; Gusev, A.; Day, F.R.; Loh, P.-R.; Duncan, L.; Perry, J.R.B.; Patterson, N.; Robinson, E.B.; et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 2015, 47, 1236–1241. [Google Scholar] [CrossRef]
- Hartz, S.M.; Horton, A.C.; Hancock, D.B.; Baker, T.B.; Caporaso, N.E.; Chen, L.-S.; Hokanson, J.E.; Lutz, S.M.; Marazita, M.L.; McNeil, D.W.; et al. Genetic correlation between smoking behaviors and schizophrenia. Schizophr. Res. 2018, 194, 86–90. [Google Scholar] [CrossRef]
- Schmitz, L.L.; Gard, A.M.; Ware, E.B. Examining sex differences in pleiotropic effects for depression and smoking using polygenic and gene-region aggregation techniques. Am. J. Med. Genet. B Neuropsychiatr. Genet. 2019, 180, 448–468. [Google Scholar] [CrossRef] [PubMed]
- Howard, D.M.; Adams, M.J.; Shirali, M.; Clarke, T.-K.; Marioni, R.E.; Davies, G.; Coleman, J.R.I.; Alloza, C.; Shen, X.; Barbu, M.C.; et al. Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nat. Commun. 2018, 9, 1470, Erratum in Nat. Commun. 2021, 12, 2012. [Google Scholar] [CrossRef] [PubMed]
- Lutz, S.M.; Vansteelandt, S.; Lange, C. Testing for direct genetic effects using a screening step in family-based association studies. Front. Genet. 2013, 4, 243. [Google Scholar] [CrossRef]
- Vansteelandt, S.; Goetgeluk, S.; Lutz, S.; Waldman, I.; Lyon, H.; Schadt, E.E.; Weiss, S.T.; Lange, C. On the adjustment for covariates in genetic association analysis: A novel, simple principle to infer direct causal effects. Genet. Epidemiol. 2009, 33, 394–405. [Google Scholar] [CrossRef]
- VanderWeele, T.J. Mediation Analysis: A Practitioner’s Guide. Annu. Rev. Public Health 2016, 37, 17–32. [Google Scholar] [CrossRef]
- Imai, K.; Keele, L.; Tingley, D. A general approach to causal mediation analysis. Psychol. Methods 2010, 15, 309–334. [Google Scholar] [CrossRef]
- Tingley, D.; Yamamoto, T.; Hirose, K.; Keele, L.; Imai, K. mediation: R Package for Causal Mediation Analysis. J. Stat. Softw. 2014, 59, 1–38. [Google Scholar] [CrossRef]
- Textor, J.; van der Zander, B.; Gilthorpe, M.S.; Liśkiewicz, M.; Ellison, G.T. Robust causal inference using directed acyclic graphs: The R package ‘dagitty’. Leuk. Res. 2016, 45, 1887–1894. [Google Scholar] [CrossRef]
- Baron, R.M.; Kenny, D.A. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Pers. Soc. Psychol. 1986, 51, 1173–1182. [Google Scholar] [CrossRef]
- Muller, D.; Judd, C.M.; Yzerbyt, V.Y. When moderation is mediated and mediation is moderated. J. Pers. Soc. Psychol. 2005, 89, 852–863. [Google Scholar] [CrossRef]
- Preacher, K.J.; Rucker, D.D.; Hayes, A.F. Addressing Moderated Mediation Hypotheses: Theory, Methods, and Prescriptions. Multivar. Behav. Res. 2007, 42, 185–227. [Google Scholar] [CrossRef]
- James, L.R.; Brett, J.M. Mediators, Moderators, and Tests for Mediation. J. Appl. Psychol. 1984, 69, 307. [Google Scholar] [CrossRef]
- Hayes, A.F. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach; The Guilford Press: New York, NY, USA, 2013. [Google Scholar]
- Sudlow, C.; Gallacher, J.; Allen, N.; Beral, V.; Burton, P.; Danesh, J.; Downey, P.; Elliott, P.; Green, J.; Landray, M.; et al. 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, e1001779. [Google Scholar] [CrossRef]
- Regan, E.A.; Hokanson, J.E.; Murphy, J.R.; Make, B.; Lynch, D.A.; Beaty, T.H.; Curran-Everett, D.; Silverman, E.K.; Crapo, J.D. Genetic epidemiology of COPD (COPDGene) study design. COPD J. Chronic Obstr. Pulm. Dis. 2011, 7, 32–43. [Google Scholar] [CrossRef]
- Snaith, R.P. The Hospital Anxiety and Depression Scale. Health Qual. Life Outcomes 2003, 1, 29. [Google Scholar] [CrossRef]
- Rose, J.E.; Behm, F.M.; Drgon, T.; Johnson, C.; Uhl, G.R. Personalized smoking cessation: Interactions between nicotine dose, dependence and quit-success genotype score. Mol. Med. 2010, 16, 247–253. [Google Scholar] [CrossRef]
- Uhl, G.R.; Liu, Q.-R.; Drgon, T.; Johnson, C.; Walther, D.; Rose, J.E.; David, S.P.; Niaura, R.; Lerman, C. Molecular genetics of successful smoking cessation: Convergent genome-wide association study results. Arch. Gen. Psychiatry 2008, 65, 683–693. [Google Scholar] [CrossRef] [PubMed]
- Pasman, J.A.; Demange, P.A.; Guloksuz, S.; Willemsen, A.H.M.; Abdellaoui, A.; Have, M.T.; Hottenga, J.-J.; Boomsma, D.I.; de Geus, E.; Bartels, M.; et al. Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status. Behav. Genet. 2022, 52, 92–107. [Google Scholar] [CrossRef] [PubMed]
- Erzurumluoglu, A.M.; Liu, M.; Jackson, V.E.; Barnes, D.R.; Datta, G.; Melbourne, C.A.; Young, R.; Batini, C.; Surendran, P.; Jiang, T.; et al. Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. Mol. Psychiatry 2020, 25, 2392–2409. [Google Scholar] [CrossRef] [PubMed]
- Liu, M.; Jiang, Y.; Wedow, R.; Li, Y.; Brazel, D.M.; Chen, F.; Datta, G.; Davila-Velderrain, J.; McGuire, D.; Tian, C.; et al. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nat. Genet. 2019, 51, 237–244. [Google Scholar] [CrossRef] [PubMed]
- Brazel, D.M.; Jiang, Y.; Hughey, J.M.; Turcot, V.; Zhan, X.; Gong, J.; Batini, C.; Weissenkampen, J.D.; Liu, M.; Barnes, D.R.; et al. Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use. Biol. Psychiatry 2019, 85, 946–955. [Google Scholar] [CrossRef] [PubMed]
- Xu, K.; Li, B.; McGinnis, K.A.; Vickers-Smith, R.; Dao, C.; Sun, N.; Kember, R.L.; Zhou, H.; Becker, W.C.; Gelernter, J.; et al. Genome-wide association study of smoking trajectory and meta-analysis of smoking status in 842,000 individuals. Nat. Commun. 2020, 11, 5302. [Google Scholar] [CrossRef] [PubMed]
- Cai, N.; Revez, J.A.; Adams, M.J.; Andlauer, T.F.M.; Breen, G.; Byrne, E.M.; Clarke, T.-K.; Forstner, A.J.; Grabe, H.J.; Hamilton, S.P.; et al. Minimal phenotyping yields genome-wide association signals of low specificity for major depression. Nat. Genet. 2020, 52, 437–447. [Google Scholar] [CrossRef] [PubMed]
- Linnér, R.K.; Biroli, P.; Kong, E.; Meddens, S.F.W.; Wedow, R.; Fontana, M.A.; Lebreton, M.; Tino, S.P.; Abdellaoui, A.; Hammerschlag, A.R.; et al. Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nat. Genet. 2019, 51, 245–257. [Google Scholar] [CrossRef] [PubMed]
- Kichaev, G.; Bhatia, G.; Loh, P.-R.; Gazal, S.; Burch, K.; Freund, M.K.; Schoech, A.; Pasaniuc, B.; Price, A.L. Leveraging Polygenic Functional Enrichment to Improve GWAS Power. Am. J. Hum. Genet. 2019, 104, 65–75. [Google Scholar] [CrossRef]
- Hulka, L.M.; Treyer, V.; Scheidegger, M.; Preller, K.H.; Vonmoos, M.; Baumgartner, M.R.; Johayem, A.; Ametamey, S.M.; Buck, A.; Seifritz, E.; et al. Smoking but not cocaine use is associated with lower cerebral metabotropic glutamate receptor 5 density in humans. Mol. Psychiatry 2014, 19, 625–632. [Google Scholar] [CrossRef]
- Uhl, G.R.; Drgon, T.; Johnson, C.; Walther, D.; David, S.P.; Aveyard, P.; Murphy, M.; Johnstone, E.C.; Munafò, M.R. Genome-wide association for smoking cessation success: Participants in the Patch in Practice trial of nicotine replacement. Pharmacogenomics 2010, 11, 357–367, Erratum in Pharmacogenomics 2010, 11, 730. [Google Scholar] [CrossRef] [PubMed]
- Huang, C.C.; Hsu, K.S. Sustained activation of metabotropic glutamate receptor 5 and protein tyrosine phosphatases mediate the expression of (S)-3,5-dihydroxyphenylglycine-induced long-term depression in the hippocampal CA1 region. J. Neurochem. 2006, 96, 179–194. [Google Scholar] [CrossRef] [PubMed]
- Chandley, M.J.; Szebeni, A.; Szebeni, K.; Crawford, J.D.; Stockmeier, C.A.; Turecki, G.; Kostrzewa, R.M.; Ordway, G.A. Elevated gene expression of glutamate receptors in noradrenergic neurons from the locus coeruleus in major depression. Int. J. Neuropsychopharmacol. 2014, 17, 1569–1578. [Google Scholar] [CrossRef] [PubMed]
- Paul, I.A.; Skolnick, P. Glutamate and depression: Clinical and preclinical studies. Ann. N. Y. Acad. Sci. 2003, 1003, 250–272. [Google Scholar] [CrossRef]
UK Biobank | COPDGene | |
---|---|---|
Sample size, N | 97,330 | 3829 |
Depression, N [%] | 38,999 [40.1%] | 1270 [33.2%] |
Sex (male), N [%] | 51,292 [52.7%] | 1941 [50.7%] |
Age, mean [SD] | 57.7 [7.8] | 67.7 [8.3] |
Current Smoker, N [%] | 25,869 [26.6%] | 1050 [27.4%] |
Pack-years, mean [SD] | 23.9 [18.6] | 46.3 [24.7] |
Location: Urban, N [%] | 83,188 [86.6%] | 3613 [94.4%] |
Income: Low, N [%] | 22,888 [23.8%] | 639 [16.7%] |
Income: Not low, N [%] | 61,166 [63.7%] | 2721 [71.1%] |
Income: Not disclosed, N [%] | 11,966 [12.5%] | 468 [12.2%] |
Education: College degree or greater, N [%] | 23,125 [24.1%] | 1814 [47.4%] |
Chr | Marker | Gene/Nearest Gene | Position | Allele Freq. | Prev. Smok. Assoc. ** | Indirect Effect (All) | Indirect Effect (Female) | Indirect Effect (Male) | Sex-Moderated Indirect Effect | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
β | 95% CI | p | β | 95% CI | p | β | 95% CI | p | β | 95% CI | p | ||||||
1 | rs10127497 | SGIP1 | 66584461 | 0.14 | 32 | −8.5 × 10−6 | (−4.2 × 10−4, 4.1 × 10−4) | 0.99 | −2.4 × 10−5 | (−7.2 × 10−4, 6.7 × 10−4) | 0.94 | −3.0 × 10−6 | (−4.9 × 10−4, 5.0 × 10−4) | 0.98 | −1.1 × 10−6 | (−8.3 × 10−4, 6.9 × 10−4) | 0.87 |
1 | rs6699744 | LOC105378797 | 72359461 | 0.61 | - | 1.7 × 10−4 | (−1.3 × 10−4, 4.5 × 10−4) | 0.27 | 2.1 × 10−4 | (−2.8 × 10−4, 7.3 × 10−4) | 0.43 | 1.3 × 10−4 | (−1.9 × 10−4, 4.8 × 10−4) | 0.42 | −1.9 × 10−5 | (−6.1 × 10−4, 6.3 × 10−4) | 0.94 |
1 | rs6424532 | LOC105378800 | 73198339 | 0.49 | - | 4.9 × 10−4 | (2.1 × 10−4, 7.7 × 10−4) | 4.0 × 10−4 | 5.7 × 10−4 | (1.1 × 10−4, 1.1 × 10−3) | 0.02 | 4.1 × 10−4 | (1.1 × 10−4, 7.4 × 10−4) | 4.0 × 10−3 | −1.1 × 10−4 | (−6.3 × 10−4, 4.6 × 10−4) | 0.76 |
1 | rs7548151 | ASTN1 | 177057847 | 0.08 | 32, 33 | 3.7 × 10−4 | (−1.6 × 10−4, 8.8 × 10−4) | 0.17 | 1.4 × 10−4 | (−7.5 × 10−4, 1.1 × 10−3) | 0.79 | 5.1 × 10−4 | (−7.6 × 10−5, 1.1 × 10−3) | 0.11 | 3.9 × 10−4 | (−5.5 × 10−4, 1.3 × 10−3) | 0.51 |
5 | rs40465 | LOC105379109 | 104646025 | 0.33 | - | −6.5 × 10−5 | (−3.6 × 10−4, 2.4 × 10−4) | 0.69 | −8.2 × 10−5 | (−5.7 × 10−4, 4.7 × 10−4) | 0.83 | −5.5 × 10−5 | (−3.9 × 10−4, 3.0 × 10−4) | 0.72 | 4.6 × 10−5 | (−6.6 × 10−4, 7.0 × 10−4) | 0.88 |
6 | rs3132685 | HCG9 | 29978172 | 0.13 | - | 3.7 × 10−4 | (−4.3 × 10−5, 7.9 × 10−4) | 0.08 | 5.6 × 10−4 | (−1.5 × 10−4, 1.4 × 10−3) | 0.12 | 2.1 × 10−4 | (−2.6 × 10−4, 6.7 × 10−4) | 0.41 | −3.5 × 10−4 | (−1.3 × 10−3, 5.3 × 10−4) | 0.38 |
6 | rs112348907 | KCNQ5 | 72878230 | 0.30 | 32 | −2.4 × 10−5 | (−3.3 × 10−4, 2.9 × 10−4) | 0.90 | 6.3 × 10−5 | (−4.5 × 10−4, 6.2 × 10−4) | 0.78 | −6.8 × 10−5 | (−4.2 × 10−4, 2.6 × 10−4) | 0.67 | −1.3 × 10−4 | (−8.0 × 10−4, 4.9 × 10−4) | 0.78 |
7 | rs3807865 | TMEM106B | 12210776 | 0.41 | - | 1.9 × 10−4 | (−9.9 × 10−5, 4.6 × 10−4) | 0.18 | 4.2 × 10−4 | (−9.4 × 10−5, 9.2 × 10−4) | 0.10 | 4.8 × 10−5 | (−2.7 × 10−4, 3.6 × 10−4) | 0.78 | −3.7 × 10−4 | (−8.9 × 10−4, 1.5 × 10−4) | 0.26 |
7 | rs2402273 | LSM8/ CTTNBP2 | 117960370 | 0.41 | 32, 34–41 | 2.5 × 10−4 | (−7.5 × 10−6, 5.3 × 10−4) | 0.06 | −6.1 × 10−5 | (−5.6 × 10−4, 4.5 × 10−4) | 0.81 | 4.4 × 10−4 | (1.2 × 10−4, 7.6 × 10−4) | 4.1 × 10−3 | 5.2 × 10−4 | (4.2 × 10−5, 1.1 × 10−3) | 0.05 |
9 | rs263575 | BNC2/CNTLN | 17033842 | 0.46 | 32, 33 | −2.4 × 10−4 | (−5.3 × 10−4, 3.1 × 10−5) | 0.08 | −5.6 × 10−4 | (−1.1 × 10−3,−6.2 × 10−5) | 0.03 | −3.7 × 10−5 | (−3.6 × 10−4, 3.1 × 10−4) | 0.82 | 5.1 × 10−4 | (5.3 × 10−6, 1.1 × 10−3) | 0.05 |
10 | rs1021363 | SORCS3 | 104851081 | 0.64 | 32 | −2.8 × 10−4 | (−5.8 × 10−4, 8.9 × 10−6) | 0.06 | −3.9 × 10−4 | (−8.7 × 10−4, 1.7 × 10−4) | 0.15 | −2.1 × 10−4 | (−5.3 × 10−4, 1.2 × 10−4) | 0.22 | 2.1 × 10−4 | (−4.2 × 10−4, 9.1 × 10−4) | 0.45 |
11 | rs10501696 | GRM5 | 89014994 | 0.50 | 32, 42, 43 | −3.7 × 10−4 | (−6.7 × 10−4, −7.2 × 10−5) | 0.01 | −8.0 × 10−4 | (−1.3 × 10−3, −2.9 × 10−4) | 2.2 × 10−3 | −8.6 × 10−5 | (−4.2 × 10−4, 2.4 × 10−4) | 0.57 | 7.1 × 10−4 | (1.7 × 10−4, 1.3 × 10−3) | 0.01 |
13 | rs9530139 | B3GLCT | 31273187 | 0.19 | 32 | −7.3 × 10−5 | (−4.1 × 10−4, 3.0 × 10−4) | 0.71 | −3.1 × 10−4 | (−9.6 × 10−4, 2.6 × 10−4) | 0.32 | 7.4 × 10−5 | (−3.1 × 10−4, 5.0 × 10−4) | 0.73 | 4.0 × 10−4 | (−3.2 × 10−4, 1.2 × 10−3) | 0.30 |
15 | rs28541419 | MRPL46 | 88402647 | 0.23 | 32 | 1.4 × 10−4 | (−2.0 × 10−4, 4.9 × 10−4) | 0.35 | −5.8 × 10−5 | (−6.3 × 10−4, 5.3 × 10−4) | 0.86 | 2.5 × 10−4 | (−9.0 × 10−5, 6.4 × 10−4) | 0.17 | 2.9 × 10−4 | (−4.1 × 10−4, 9.5 × 10−4) | 0.46 |
Chr | Marker | Gene/Nearest Gene | Position | Allele Freq. | Prev. Smok. Assoc. ** | Indirect Effect (All) | Indirect Effect (Female) | Indirect Effect (Male) | Sex-Moderated Indirect Effect | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
β | 95% CI | p | β | 95% CI | p | β | 95% CI | p | β | 95% CI | p | ||||||
1 | rs10127497 | SGIP1 | 66584461 | 0.14 | 32 | −1.0 × 10−4 | (−1.8 × 10−3, 1.6 × 10−3) | 0.89 | −7.2 × 10−4 | (−4.4 × 10−3, 2.4 × 10−3) | 0.64 | 1.9 × 10−4 | (−1.4 × 10−3, 2.0 × 10−3) | 0.77 | 3.1 × 10−4 | (−2.2 × 10−3, 2.9 × 10−3) | 0.87 |
1 | rs12143898 * | LOC105378797 | 72360489 * | 0.20 | - | 2.3 × 10−4 | (−1.2 × 10−3, 1.6 × 10−3) | 0.73 | −8.3 × 10−4 | (−4.0 × 10−3, 1.7 × 10−3) | 0.58 | 5.6 × 10−4 | (−6.7 × 10−4, 2.8 × 10−3) | 0.44 | 1.5 × 10−3 | (−5.3 × 10−4, 4.6 × 10−3) | 0.19 |
1 | rs12044445 * | LOC105378800 | 73200931 * | 0.47 | - | 8.1 × 10−5 | (−1.1 × 10−3, 1.4 × 10−3) | 0.84 | −8.9 × 10−4 | (−3.6 × 10−3, 1.2 × 10−3) | 0.41 | 4.3 × 10−4 | (−5.4 × 10−4, 2.0 × 10−3) | 0.45 | 8.6 × 10−4 | (−7.0 × 10−4, 3.0 × 10−3) | 0.31 |
1 | rs7548151 | ASTN1 | 177057847 | 0.09 | 32, 33 | −4.2 × 10−4 | (−2.6 × 10−3, 1.7 × 10−3) | 0.70 | −8.3 × 10−4 | (−5.6 × 10−3, 3.6 × 10−3) | 0.71 | −2.4 × 10−4 | (−2.7 × 10−3, 1.7 × 10−3) | 0.82 | 4.3 × 10−4 | (−3.4 × 10−3, 3.8 × 10−3) | 0.91 |
5 | rs40465 | LOC105379109 | 104646025 | 0.33 | - | 1.1 × 10−3 | (3.8 × 10−5, 2.6 × 10−3) | 0.05 | 3.0 × 10−3 | (5.3 × 10−4, 6.6 × 10−3) | 0.02 | 1.4 × 10−4 | (−1.0 × 10−3, 1.5 × 10−3) | 0.76 | −1.6 × 10−3 | (−4.4 × 10−3, 6.1 × 10−4) | 0.18 |
6 | rs112348907 | KCNQ5 | 72878230 | 0.29 | - | 1.2 × 10−3 | (−6.4 × 10−5, 3.1 × 10−3) | 0.07 | 7.4 × 10−4 | (−1.7 × 10−3, 3.4 × 10−3) | 0.51 | 1.3 × 10−3 | (−4.6 × 10−4, 4.2 × 10−3) | 0.18 | 6.9 × 10−4 | (−1.6 × 10−3, 3.2 × 10−3) | 0.46 |
7 | rs3807865 | TMEM106B | 12210776 | 0.41 | 32 | −4.5 × 10−4 | (−1.7 × 10−3, 6.5 × 10−4) | 0.44 | 4.8 × 10−4 | (−1.9 × 10−3, 3.1 × 10−3) | 0.68 | −7.1 × 10−4 | (−2.7 × 10−3, 4.2 × 10−4) | 0.28 | −1.1 × 10−3 | (−3.7 × 10−3, 9.0 × 10−4) | 0.30 |
7 | rs2402273 | LSM8/ CTTNBP2 | 117960370 | 0.42 | - | 6.9 × 10−4 | (−4.0 × 10−4, 2.0 × 10−3) | 0.27 | 4.5 × 10−4 | (−2.1 × 10−3, 2.9 × 10−3) | 0.69 | 5.5 × 10−4 | (−4.5 × 10−4, 2.3 × 10−3) | 0.37 | 3.1 × 10−4 | (−2.5 × 10−3, 3.1 × 10−3) | 0.81 |
9 | rs263575 | BNC2/CNTLN | 17033842 | 0.45 | 32, 34–41 | −1.8 × 10−4 | (−1.4 × 10−3, 1.0 × 10−3) | 0.79 | 4.1 × 10−4 | (−1.9 × 10−3, 2.8 × 10−3) | 0.75 | −3.5 × 10−4 | (−2.2 × 10−3, 6.7 × 10−4) | 0.58 | −5.0 × 10−4 | (−2.3 × 10−3, 1.1 × 10−3) | 0.64 |
10 | rs79699572 * | SORCS3 | 105109590 * | 0.03 | 32, 33 | −3.1 × 10−3 | (−6.9 × 10−3, −4.1 × 10−5) | 0.04 | −4.7 × 10−3 | (−0.01, 9.4 × 10−4) | 0.12 | −1.7 × 10−3 | (−6.7 × 10−3, 1.4 × 10−3) | 0.36 | 7.8 × 10−4 | (−5.3 × 10−3, 6.9 × 10−3) | 0.77 |
11 | rs180838672 * | GRM5 | 88584239 * | 0.01 | 32 | −9.0 × 10−3 | (−0.02, −1.1 × 10−3) | 0.02 | −0.02 | (−0.04, 2.2 × 10−3) | 0.10 | −4.2 × 10−3 | (−0.01, 2.4 × 10−3) | 0.24 | 8.4 × 10−3 | (−7.4 × 10−3, 0.03) | 0.40 |
13 | rs9530139 | B3GLCT | 31273187 | 0.19 | 32, 42, 43 | −1.1 × 10−3 | (−3.0 × 10−3, 3.4 × 10−4) | 0.15 | −1.4 × 10−3 | (−4.6 × 10−3, 1.6 × 10−3) | 0.36 | −8.1 × 10−4 | (−3.1 × 10−3, 5.5 × 10−4) | 0.33 | −3.8 × 10−6 | (−2.8 × 10−3, 3.3 × 10−3) | 0.92 |
15 | rs28541419 | MRPL46 | 88402647 | 0.24 | 32 | −1.1 × 10−3 | (−2.9 × 10−3, 2.9 × 10−4) | 0.12 | −1.4 × 10−3 | (−4.6 × 10−3, 1.3 × 10−3) | 0.31 | −7.8 × 10−4 | (−2.9 × 10−3, 4.4 × 10−4) | 0.29 | 3.4 × 10−4 | (−1.9 × 10−3, 3.1 × 10−3) | 0.84 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Voorhies, K.; Hecker, J.; Lee, S.; Hahn, G.; Prokopenko, D.; McDonald, M.-L.; Wu, A.C.; Wu, A.; Hokanson, J.E.; Cho, M.H.; et al. Examining the Effect of Genes on Depression as Mediated by Smoking and Modified by Sex. Genes 2024, 15, 565. https://doi.org/10.3390/genes15050565
Voorhies K, Hecker J, Lee S, Hahn G, Prokopenko D, McDonald M-L, Wu AC, Wu A, Hokanson JE, Cho MH, et al. Examining the Effect of Genes on Depression as Mediated by Smoking and Modified by Sex. Genes. 2024; 15(5):565. https://doi.org/10.3390/genes15050565
Chicago/Turabian StyleVoorhies, Kirsten, Julian Hecker, Sanghun Lee, Georg Hahn, Dmitry Prokopenko, Merry-Lynn McDonald, Alexander C. Wu, Ann Wu, John E. Hokanson, Michael H. Cho, and et al. 2024. "Examining the Effect of Genes on Depression as Mediated by Smoking and Modified by Sex" Genes 15, no. 5: 565. https://doi.org/10.3390/genes15050565
APA StyleVoorhies, K., Hecker, J., Lee, S., Hahn, G., Prokopenko, D., McDonald, M.-L., Wu, A. C., Wu, A., Hokanson, J. E., Cho, M. H., Lange, C., Hoth, K. F., & Lutz, S. M. (2024). Examining the Effect of Genes on Depression as Mediated by Smoking and Modified by Sex. Genes, 15(5), 565. https://doi.org/10.3390/genes15050565