亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

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

不育 男性不育 孟德尔随机化 单核苷酸多态性 人口 睾酮(贴片) 医学 性激素结合球蛋白 生理学 妇科 生物 遗传学 内科学 基因型 怀孕 激素 雄激素 遗传变异 环境卫生 基因
作者
Yang Xiong,Xiaokun Hu,Yangchang Zhang,Feng Qin,Jiuhong Yuan
出处
期刊:MedComm [Wiley]
卷期号:4 (5) 被引量:1
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.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
汉堡包应助鲸落Oo采纳,获得10
刚刚
HK发布了新的文献求助10
1秒前
123mmmm发布了新的文献求助10
4秒前
科研通AI6应助等乙天采纳,获得10
4秒前
默默冬瓜完成签到,获得积分10
7秒前
12秒前
风清扬发布了新的文献求助10
12秒前
14秒前
VVV发布了新的文献求助10
17秒前
风中的小鸽子完成签到 ,获得积分10
17秒前
科研通AI2S应助HK采纳,获得10
18秒前
19秒前
19秒前
如闪电般归来完成签到,获得积分10
20秒前
鲸落Oo发布了新的文献求助10
20秒前
Abdurrahman完成签到,获得积分10
23秒前
Kannan发布了新的文献求助10
24秒前
Lemon181完成签到,获得积分10
25秒前
28秒前
29秒前
31秒前
嘿嘿应助科研通管家采纳,获得10
31秒前
31秒前
嘿嘿应助科研通管家采纳,获得10
32秒前
嘿嘿应助科研通管家采纳,获得10
32秒前
嘿嘿应助科研通管家采纳,获得10
32秒前
123mmmm发布了新的文献求助10
32秒前
细心的绣连关注了科研通微信公众号
34秒前
36秒前
wanci应助Kannan采纳,获得10
40秒前
夜霖凛发布了新的文献求助100
41秒前
123mmmm完成签到,获得积分10
41秒前
等乙天发布了新的文献求助10
42秒前
sj发布了新的文献求助10
44秒前
45秒前
杨天天完成签到 ,获得积分10
46秒前
HK完成签到,获得积分10
47秒前
风清扬发布了新的文献求助10
47秒前
归雁完成签到,获得积分10
48秒前
陈欣瑶完成签到 ,获得积分10
50秒前
高分求助中
Encyclopedia of Immunobiology Second Edition 5000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 临床微生物学程序手册,多卷,第5版 2000
List of 1,091 Public Pension Profiles by Region 1621
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] | NHBS Field Guides & Natural History 1500
The Victim–Offender Overlap During the Global Pandemic: A Comparative Study Across Western and Non-Western Countries 1000
Lloyd's Register of Shipping's Approach to the Control of Incidents of Brittle Fracture in Ship Structures 1000
Brittle fracture in welded ships 1000
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5584578
求助须知:如何正确求助?哪些是违规求助? 4668351
关于积分的说明 14771240
捐赠科研通 4611160
什么是DOI,文献DOI怎么找? 2530000
邀请新用户注册赠送积分活动 1498932
关于科研通互助平台的介绍 1467441