No genetic causal association between COVID‐19 infection, hypogonadism, and male infertility

不育 2019年冠状病毒病(COVID-19) 男性不育 联想(心理学) 医学 生物 遗传学 内科学 心理学 怀孕 疾病 传染病(医学专业) 心理治疗师
作者
Yang Xiong,Xiang Hu,Yangchang Zhang,QiPing Feng,Jiuhong Yuan
出处
期刊:MedComm [Wiley]
卷期号:4 (5)
标识
DOI:10.1002/mco2.389
摘要

Dear Editor: SARS-CoV-2 infection has been observed to induce testicular damage, leading to a reduction in serum testosterone levels and sperm count.1 While the potential for hypogonadism and subfertility has been acknowledged, it remains inadequately assessed. Clinical studies present inconsistent findings regarding the relationship between COVID-19 infection, hypogonadism, and male infertility.2 The true association between COVID-19 infection, hypogonadism, and infertility remains unclear. To address the limitations of observational design, we employed the Mendelian Randomization (MR) approach in this study. MR is a method using single nucleotide polymorphisms (SNPs) as genetic proxies to substitute the exposures (i.e., COVID-19 infection) and the outcomes (i.e., testosterone and male infertility).3 During gestation, SNPs closely associated with COVID-19 infection, hypogonadism, and male infertility are distributed at random, which are not interfered by postnatal confounders.3 Therefore, within the framework of MR, patients with COVID-19 infection are naturally randomized, facilitating the investigation of the risk of hypogonadism and infertility. The Genome-Wide Association Studies (GWASs) of COVID-19 susceptibility (COVID vs. population), hospitalization (hospitalized COVID vs. population), and severity (very severe cases vs. population) were retrieved from the COVID-19 Host Genetics Initiative.4 These GWASs included 1,683,768, 1,887,658, and 1,388,342 participants, respectively. The genetic associations of total testosterone (199,569 males), bioavailable testosterone (BAT, 184,205 males), and sex hormone-binding globulin (SHBG, 185,221 males) and male infertility (680 cases and 72,799 controls) were extracted from previous GWASs and the FinnGen biobank.5 The detailed information of instrumental variables (IVs, p < 5 × 10−8) is displayed in Table S1. Further information regarding the GWASs and the downloading websites for the raw data can be found in Tables S2 and S3. p < 0.05/n (0.05/12 = 0.0042) was considered statistically significant. The statistical analyses are detailed in Supporting Information. Our findings did not establish a causal link between COVID-19 infection and male infertility. The Inverse Variance Weighted (IVW) method disclosed that the odds ratios (ORs) of male infertility were 0.74 for susceptibility (95% CI = 0.32–1.69, p = 0.472), 0.79 for hospitalization (95% CI = 0.53–1.19, p = 0.268), and 0.87 for severity (95% CI = 0.69–1.09, p = 0.220), respectively (Figure 1A). The other four methods including Maximum Likelihood, MR-Egger, MR-RAPS (Robust Adjusted Profile Score), and Weighted Median were in line with the IVW model, reporting no causal association between COVID-19 infection and male infertility (all p > 0.05). Figure 1B–D illustrates an inverse correlation between the SNP effects on COVID-19 infection (susceptibility, hospitalization, and severity) and male infertility. In Table S4, the intercept terms of MR-Egger regression are close to zero (all p > 0.05), suggesting no pleiotropy. Additionally, the mean F statistics of selected IVs were greater than 48, indicating a lower likelihood of bias from weak IVs. In Figure S1, the funnel plots show symmetrical distributions of IVs. The IVW approach also reported no heterogeneity (all p > 0.05). In Figure 1E, the IVW method reveals that genetically proxied COVID-19 infection has no impact on testosterone levels (β = 0.0148 for COVID-19 susceptibility, 0.0394 for COVID-19 hospitalization, and 0.0070 for COVID-19 severity, all p > 0.05). The findings remained insignificant in most of the sensitivity analyses (all p > 0.05). The scatter plots did not exhibit a negative trend between the SNP effects on COVID-19 infection and testosterone levels (Figure S2A–C). Of note, there was significant heterogeneity in the IVs (Figure S2D–F), without pleiotropy (Table S4). Similarly, the IVW estimator found no significant associations between COVID-19 infection and BAT by the IVW method in Figure 1E (β = 0.0190 for COVID-19 susceptibility, −0.0113 for COVID-19 hospitalization, and 0.0160 for COVID-19 severity, all p > 0.05). The other four methods obtained similar results, providing no evidence that COVID-19 infection leads to a decrease in BAT levels (all p > 0.05). In Figure S3A–C, no apparent downward trend is observed between the SNP effects on COVID-19 infection and BAT. In Figure S3D–F and Table S4, significant heterogeneities are observed for the IVs of COVID-19 hospitalization and severity (p < 0.05), without evidence of pleiotropy (p > 0.05). No significant causal relationship was found between COVID-19 susceptibility and SHBG levels (β = −0.0350, 95% CI = −0.0769 to 0.0069, p = 0.101; Figure 1E). However, the IVW estimator revealed that genetically predicted COVID-19 hospitalization and severity were associated with decreased levels of SHBG (β = −0.0350, p = 0.004 and β = −0.0273, p = 0.003, respectively). The consistency in the magnitude and direction of results across MR-RAPS, Weighted Median, and Maximum Likelihood methods substantiates the risk impact of COVID-19 hospitalization and severity on SHBG levels. In Figure S4A–C, the scatter plots visualize a downward trend regarding the SNP effects between COVID-19 infection and SHBG. In Figure S4D–F and Table S4, no significant heterogeneity and pleiotropy are detected (all p > 0.05). We further performed reversed MR analyses to rule out reverse causality. In Figure S5, the IVW model shows that the increment of total testosterone, BAT, and SHBG concentrations have no effect on COVID-19 infection (susceptibility, hospitalization, and severity, all p > 0.05). The mean F statistics were all greater than 80, showing adequate strengths of IVs. In addition, the intercept terms of MR-Egger regression were close to null, indicating no pleiotropy (all p > 0.05). As shown in Figure S6, significant heterogeneities in the IVs for total testosterone, BAT, and SHBG are observed. Thus, the random-effect IVW model was used to estimate the causal effects. Notably, our study found a significant association between COVID-19 infection and decreased SHBG levels. Previous reports have associated COVID-19 infection with hepatic dysfunction.6 Given that SHBG is synthesized in the liver and transports sex hormones in serum, liver dysfunction may lead to decreased SHBG. A decline in SHBG indicates a higher concentration of free testosterone and a lower likelihood of hypogonadism and male infertility. In conclusion, our study provides causal evidence that genetically proxied COVID-19 infection does not increase the risk of hypogonadism and male infertility. Jiuhong Yuan proposed the research topic and supervised the study. Yang Xiong, Xiaokun Hu, and Yangchang Zhang performed the statistical analysis. The manuscript was written by Yang Xiong and Xiaokun Hu, and revised by Jiuhong Yuan and Feng Qin. All authors have read and approved for the final manuscript. We thank Ms. Xiaoyingzi Huang of the Andrology Lab, West China Hospital, Sichuan University, for technical assistance. The authors declare they have no conflicts of interest. Ethical review and approval were waived for this study. The entire data from Mendelian Randomization is publicly accessible (https://gwas.mrcieu.ac.uk/). Informed consent was obtained from all subjects in the original genome-wide association studies. The entire data from Mendelian Randomization is publicly accessible (https://gwas.mrcieu.ac.uk/). Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
酷波er应助专注学习采纳,获得10
2秒前
2秒前
3秒前
bkagyin应助Eourique采纳,获得10
3秒前
4秒前
CipherSage应助cauliflower采纳,获得10
5秒前
王楠楠发布了新的文献求助10
5秒前
5秒前
5秒前
ming发布了新的文献求助10
6秒前
鑫光熠熠发布了新的文献求助10
7秒前
清清旋雪完成签到 ,获得积分10
7秒前
7秒前
西贝完成签到,获得积分10
10秒前
lilibetch完成签到,获得积分10
12秒前
领导范儿应助jisimyang98采纳,获得10
12秒前
xin发布了新的文献求助10
12秒前
宝儿姐完成签到,获得积分10
12秒前
Phuctanpct关注了科研通微信公众号
12秒前
思洋完成签到,获得积分10
13秒前
13秒前
zhu96114748完成签到,获得积分10
13秒前
15秒前
15秒前
15秒前
16秒前
cauliflower发布了新的文献求助10
16秒前
天海蓝完成签到 ,获得积分10
17秒前
苏倩发布了新的文献求助10
18秒前
18秒前
赘婿应助wangyinong采纳,获得30
20秒前
朱迪发布了新的文献求助10
20秒前
wuuuuuuu发布了新的文献求助10
21秒前
刚子发布了新的文献求助10
22秒前
乐观寒珊完成签到,获得积分10
22秒前
23秒前
25秒前
春日午后完成签到,获得积分10
25秒前
26秒前
高分求助中
Evolution 10000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Distribution Dependent Stochastic Differential Equations 500
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3157989
求助须知:如何正确求助?哪些是违规求助? 2809366
关于积分的说明 7881582
捐赠科研通 2467822
什么是DOI,文献DOI怎么找? 1313728
科研通“疑难数据库(出版商)”最低求助积分说明 630522
版权声明 601943