Hussain et al1 identified 17 natural coding variants for human angiotensin‐converting enzyme 2 (ACE2 ) that were found at positions described as important for binding of ACE2 with SARS‐CoV‐2 spike protein. The authors suggested that positive prognosis of COVID‐19 may be due to the existence of ACE2 variants like rs73635825 and rs143936283 in some individuals, and that their findings provide clues to screen frequencies of candidate alleles in different populations to predict the prognosis of COVID‐19.1 We would like to contribute with further data for these 17 ACE2 variants from other function prediction tools, and to debate regarding their use in population genetic studies.

The combination of functional predictors could yield more reliable findings mainly regarding to missense variants,2 as previously reported.3 Therefore, we searched for these ACE2 variants using other recommended predictors. No data were reported by ClinVar and Clinpred, but rs73635825, rs143936283, rs4646116, and rs146676783 were predicted as tolerated by FATHMM, using the inherited disease algorithm to analyze protein missense variants. Compared to SIFT, rs73635825 was also predicted as tolerated, but rs146676783 was predicted as damaging.1 Both variants were predicted as probably damaging by PolyPhen‐2, but as likely benign by CADD and REVEL.1

The identified ACE2 variants have functional importance in binding viral spike protein to ACE2 receptor, but the reported allele frequencies are <1%.1 Table 1 shows the minor allele frequency (MAF) for different populations where these 17 ACE2 variants have already been found. Noteworthy, all of them are considered as rare (MAF <1%) genetics variants.4, 5 Rare variants do not necessarily contribute with a large fraction of the genetic variance underlying complex traits.6 However, one can expect that much of the variance to be due to rare alleles only for diseases that are caused primarily by strongly deleterious mutations.6 In this context, we understand their goal for selecting coding variants in the binding region with SARS‐CoV‐2 spike protein to ACE2 receptor.1 However, this increases the chance of selecting rare and/or low‐frequency (MAF <1%‐5%) variants,4, 5 which tend to be population or sample specific.6, 7

Conversely, population genetic studies usually focus on common variants (MAF ≥5%) that are expected to be found in different populations. Moreover, a previous study that analyzed coding variants for ACE2 showed no direct genetic evidence supporting the existence of coronavirus S‐protein binding‐resistant ACE2 mutants in different populations.8 However, it is important to highlight that this study did not include the variants identified by Hussain et al,1 and that further investigation are warranted regarding ACE2 polymorphisms.8

Indeed, the majority of associations with low‐frequency and rare variants demonstrate relatively small effects on complex traits and disease.9 Despite limitations of power and resolution, rare variant association studies are becoming increasingly mature, which have been carried out with multiple alleles of different genes in many different populations.9 For example, the rare‐variant analytical approaches allow the identification of genes containing an excess of rare and presumably deleterious variation among cases ascertained for complex disease traits, relative to controls.10 There is little evolutionary time for SARS‐CoV‐2 contact with humans, so not enough time for selective pressure. In addition, not all the variants described were described as deleterious,1 their effects are unknown and they did not passed through the filters of qualifying a variant used by these approaches.10

Therefore, although different approaches are being developed to evaluate the use of rare variants in population studies^10, rare variants may not be suitable markers for population genetic studies and demographic differentiation related to COVID‐19. For example, the low MAF for these 17 ACE2 rare variants (Table 1) may hinder analysis such as linkage disequilibrium maps used to assess the nonrandom association of alleles at different loci, which could be used to examine the correlation between ACE2 variants as a factor resistance or susceptibility against COVID‐19 in different populations. Moreover, the absence of reported pathogenicity for these ACE2 variants according to several predictors suggest they may not provide protection in a level that explains the differences in infection rates and mortality among the affected countries, as described by World Health Organization (https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports).

Finally, the differences in incidence and clinical manifestations found among countries, sex and age groups may be due to interactions in genetic pathways in addition to social/economics factors. Nevertheless, COVID‐19 is a recent and major health problem with serious economic and social consequences, which requires efforts in the various fields of science, including further population genetic studies on the relationship of SARS‐COV‐2 and ACE2 to better assess the eventual susceptibility to SARS‐COV‐2 infection.

Hussain 等人1确定了人血管紧张素转换酶 2 ( ACE2 ) 的 17 种天然编码变体，这些变体位于被描述为 ACE2 与 SARS-CoV-2 刺突蛋白结合的重要位置。作者提出，COVID-19 的积极预后可能是由于某些个体中存在rs73635825 和 rs143936283 等ACE2变异，他们的发现为筛选不同人群中候选等位基因的频率以预测 COVID-19 的预后提供了线索. 1我们愿意为来自其他功能预测工具的这 17 种ACE2变体提供更多数据，并讨论它们在群体遗传研究中的用途。

功能预测因子的组合可以产生更可靠的发现，主要与错义变异有关，2正如之前报道的那样。3因此，我们使用其他推荐的预测因子搜索了这些ACE2变体。ClinVar 和 Clinpred 没有报告数据，但 rs73635825、rs143936283、rs4646116 和 rs146676783 被预测为 FATHMM 耐受，使用遗传病算法分析蛋白质错义变异。与 SIFT 相比，rs73635825 也被预测为可耐受的，但 rs146676783 被预测为具有破坏性。1 PolyPhen-2 预测这两种变体可能具有破坏性，但 CADD 和 REVEL 预测它们可能是良性的。1个

已鉴定的ACE2变体在将病毒刺突蛋白与 ACE2 受体结合方面具有重要的功能，但报道的等位基因频率 <1%。1表 1 显示了已发现这 17 种ACE2变体的不同人群的次要等位基因频率 (MAF) 。值得注意的是，所有这些都被认为是罕见的 (MAF <1%) 遗传变异。4, 5罕见变异不一定对复杂性状的大部分遗传变异有贡献。6然而，人们可以预计，只有对于主要由强烈有害突变引起的疾病而言，大部分差异是由于罕见的等位基因造成的。6个在这种情况下，我们理解他们的目标是在 SARS-CoV-2 刺突蛋白与 ACE2 受体的结合区域中选择编码变体。1然而，这增加了选择稀有和/或低频率（MAF <1%‐5%）变异的机会，4、5往往是特定于人群或样本的。6, 7

相反，群体遗传学研究通常侧重于预计会在不同人群中发现的常见变异 (MAF ≥ 5%)。此外，之前一项分析ACE2编码变异的研究表明，没有直接的遗传证据支持冠状病毒 S 蛋白结合抗性ACE2突变体在不同人群中的存在。8然而，必须强调的是，这项研究不包括 Hussain 等人1确定的变异，并且需要对ACE2多态性进行进一步调查。8个

事实上，大多数与低频和罕见变异的关联表明对复杂性状和疾病的影响相对较小。9尽管功效和分辨率有限，但罕见变异关联研究正变得越来越成熟，这些研究已在许多不同人群中对不同基因的多个等位基因进行了研究。9例如，相对于对照，罕见变异分析方法允许在确定为复杂疾病特征的病例中识别含有过量罕见且可能有害变异的基因。10SARS-CoV-2 与人类接触的进化时间很短，因此没有足够的时间来施加选择压力。此外，并非所有描述的变体都被描述为有害1 ，它们的影响是未知的，并且它们没有通过这些方法所使用的变体的限定过滤器。10

因此，尽管正在开发不同的方法来评估稀有变异在人群研究中的使用^10，但稀有变异可能不适合用于与 COVID-19 相关的人群遗传研究和人口分化的标记。例如，这 17 种ACE2罕见变异的低 MAF（表 1）可能会阻碍分析，例如用于评估不同位点等位基因非随机关联的连锁不平衡图，这可用于检查 ACE2 变异之间的相关性作为一个因素不同人群对 COVID-19 的耐药性或易感性。此外，没有报道这些ACE2的致病性根据几个预测因素的变异表明，它们可能无法提供解释受影响国家感染率和死亡率差异的水平，如世界卫生组织所述 (https://www.who.int/emergencies/diseases/novel -coronavirus-2019/situation-reports）。

最后，在国家、性别和年龄组之间发现的发病率和临床表现的差异可能是由于除了社会/经济因素之外遗传途径的相互作用。尽管如此，COVID-19 是最近出现的一个重大健康问题，具有严重的经济和社会后果，这需要各个科学领域的努力，包括对 SARS-COV-2 和 ACE2 的关系进行进一步的人口遗传学研究，以更好地评估最终的结果。对 SARS-COV-2 感染的易感性。