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. 2022 Jul 22;94(11):5225–5243. doi: 10.1002/jmv.27976

Analysis of ACE2 and TMPRSS2 coding variants as a risk factor for SARS‐CoV‐2 from 946 whole‐exome sequencing data in the Turkish population

Nilgun Duman 1, Gulten Tuncel 2, Atil Bisgin 3,4, Sevcan Tug Bozdogan 3,4, Sebnem Ozemri Sag 5, Seref Gul 6, Aslihan Kiraz 7, Burhan Balta 7, Murat Erdogan 7, Bulent Uyanik 8, Sezin Canbek 9, Pinar Ata 10, Bilgen Bilge Geckinli 10, Esra Arslan Ates 10, Ceren Alavanda 10, Sevda Yesim Ozdemir 11, Ozlem Sezer 12, Gulay Oner Ozgon 13, Hakan Gurkan 14, Kubra Guler 15, Ibrahim Boga 3,4, Niyazi Kaya 5, Adem Alemdar 5, Murat Sayan 2,16, Munis Dundar 17, Mahmut Cerkez Ergoren 2,18,✉, Sehime Gulsun Temel 5,18,19,20,✉
PMCID: PMC9349697  PMID: 35811452

Abstract

Heterogeneity in symptoms associated with COVID‐19 in infected patients remains unclear. ACE2 and TMPRSS2 gene variants are considered possible risk factors for COVID‐19. In this study, a retrospective comparative genome analysis of the ACE2 and TMPRSS2 variants from 946 whole‐exome sequencing data was conducted. Allele frequencies of all variants were calculated and filtered to remove variants with allele frequencies lower than 0.003 and to prioritize functional coding variants. The majority of detected variants were intronic, only two ACE2 and three TMPRSS2 nonsynonymous variants were detected in the analyzed cohort. The main ACE2 variants that putatively have a protective or susceptibility effect on SARS‐CoV‐2 have not yet been determined in the Turkish population. The Turkish genetic makeup likely lacks any ACE2 variant that increases susceptibility to SARS‐CoV‐2 infection. TMPRSS2 rs75603675 and rs12329760 variants that were previously defined as common variants that have different allele frequencies among populations and may have a role in SARS‐CoV‐2 attachment to host cells were determined in the population. Overall, these data will contribute to the formation of a national variation database and may also contribute to further studies of ACE2 and TMPRSS2 in the Turkish population and differences in SARS‐CoV‐2 infection among other populations.

Keywords: ACE2, COVID‐19, SARS‐CoV‐2, TMPRSS2, variant

1. INTRODUCTION

After the pneumonia cases of unknown cause were reported to the World Health Organization (WHO) in Wuhan Province of China in December 2019, the factor causing the disease was identified as a novel coronavirus strain. Cases were spread worldwide and the WHO declared a pandemic on March 11, 2020. The new coronavirus strain was named SARS‐CoV‐2 as they share a remarkable genetic identity with the known SARS‐CoV and the disease was referred to as coronavirus disease 2019 (COVID‐19). 1 SARS‐CoV‐2, which has a much higher transmission rate than the known human coronavirus strains, damages the lung tissue, causing respiratory failure and leading to death. Individuals over 65 years old, smokers, and people with chronic diseases such as hypertension, diabetes, and kidney failure are more severely affected. Patients commonly show symptoms of dry cough, high fever, and shortness of breath, while some patients with abdominal pain, diarrhea, and headache are also reported. Some infected individuals, on the other hand, remain asymptomatic. 2 As of the end of March 2021, the number of cases reported as SARS‐CoV‐2 positive worldwide has exceeded 128 million, and over 2 million deaths were reported to the WHO. 3

Considering the cases worldwide, it was observed that SARS‐CoV‐2 was strangely and tragically selective. While only some infected people have been reported to be sick and most of the critical patients are elderly or people with chronic problems; some of those who die from the disease are individuals who do not have any chronic disease and are relatively young. A great variation in cases and mortality rates among countries were also detected. Along with factors including the number of tests performed, percentage of smokers, average age, and environmental factors, it is thought that genetic characteristics might also affect susceptibility to SARS‐CoV‐2 infection.

The entry of enveloped viruses into cells is initiated by the binding of its spike (S) proteins to cell surface receptors. Previous reports indicated that angiotensin‐converting enzyme 2 (ACE2) is one of the host receptors for the novel coronavirus, SARS‐CoV‐2. 1 , 4 ACE2 is a transmembrane protein encoded by the ACE2 (MIM# 300335) gene on the Xp22.2 chromosome and has a transcript composed of 3339 bp and 21 exons. It is responsible for the conversion of angiotensin I to angiotensin 1−9 and angiotensin II to vasodilator angiotensin 1−7 and has roles in renal and cardiovascular function. 5 In addition to cell surface receptors, another factor required for the entry of viruses into host cells is proteases. Proteases cleave and activate viral envelope glycoproteins and form domains catalyzing membrane melding, which is a process called priming. 6 Transmembrane protease serine 2 (TMPRSS2) is shown to be involved in priming SARS‐CoV‐2 by cleaving the S protein at the S1/S2 and S2 sites. 7 TMPRSS2 is encoded by TMPRSS2 (MIM# 602060) gene on chromosome 21q22.3, producing a 3250 bp‐long transcript with 14 exons according to the NCBI database.

Expression levels and variations in ACE2 and TMPRSS2 in different individuals may facilitate or slow down the entrance of the virus into host cells and this might explain the dramatic variability of SARS‐CoV‐2 infection through individuals and populations. Likewise, variations in expression quantitative trait loci (eQTL) regions, known to regulate the ACE2 gene expression, may lead to changes in protein synthesis hence the course of infection. In a recent study, ACE2 and eQTL variation data from worldwide populations in ChinaMap, 1000 Genomes Project, and gnomAD databases were examined. Even though there is no direct evidence supporting the presence of ACE2 variations causing resistance to coronavirus S‐protein binding among populations, the study suggested that the eQTL variants associated with higher ACE2 expression have much higher allele frequencies in East Asian populations that may have an effect on different sensitivity or response from different populations to COVID‐19 under similar conditions. 8 In the Italian population, where the disease caused more severe results compared to Asian and European countries, four TMPRSS2 variants were found to have significantly different allele frequencies. Furthermore, concerning the eQTL variants, population‐specific haplotypes were detected that are expected to upregulate TMPRSS2 gene expression. 9

In light of these works, we conducted a retrospective comparative genome analysis of the ACE2 and TMPRSS2 gene variants in the Turkish population.

2. MATERIAL AND METHODS

2.1. Data collection and analysis

To investigate the allele frequencies of all functional coding variants of ACE2 and TMPRSS2, variation data from 946 unique individuals were collected from a total of 10 centers and hospitals around Turkey. As these individuals were randomly selected from centers located in various cities over the whole geographical parts of Turkey, we believe that the data represent the population of the country. This study was approved by the institutional review board (approval no: YDU/2020/79‐1103). The name of the center, sequencing platform, panels, and bioinformatic pipelines used are listed in Supporting Information: Table 1. Allele frequencies of all ACE2 and TMPRSS2 variants were calculated and then filtered to remove variants with allele frequencies lower than 0.003. Individuals with unknown gender (fetus) and without sufficient variant information were removed from the analysis. Public databases including Database of single‐nucleotide polymorphism (dbSNP), genome aggregation database (gnomAD v2.1.1), and Ensembl were used to prioritize functional coding variants and to obtain global and population‐based allele frequencies for comparison. 10 , 11 , 12

2.2. In silico analysis

Crystal structures of ACE2‐Spike (PDB ID:6LZG) and TMPRSS2 (PDB ID: 7MEQ) were retrieved from the protein data bank. PyMol program (http://pymol.sourceforge.net) was used to visualize and generate in silico mutant proteins. 13

3. RESULTS

3.1. ACE2 gene variant analysis

A total of 2948 variants from 617 individuals were analyzed and 451 different variants were detected. Among the 451 variants, 9 of them were nonsynonymous. When the variants that have allele frequencies lower than 0.003 were removed, 70 variants remained and 2 of those were missense variants, one coding sequence synonymous variant, and the others were intronic variants. Details of the 70 variants, calculated allele frequencies in the Turkish population, and global and population‐based allele frequencies obtained from public databases are represented in Table 1.

Table 1.

The list of ACE2 gene variant analysis from the whole‐exome sequencing data (only the variants ≥0.003 are listed)

dbSNP‐ID c.DNA Allele frequency Coding consequence Amino acid change g1000 GnomAD GLOBAL EUR
rs971249 c.584‐71A>G 0.581 Intronic 0.803 0.695 0.644 0.609
rs113691336, rs4646158 c.1297 + 68_1297 + 69insCTTAT 0.455 Intronic 0.834 0.729 0.629
rs4646174 c.1896 + 147G>C 0.404 Intronic 0.683 0.621 0.683 0.649
rs2285666 c.439 + 4G>A 0.326 Intronic, splice donor 0.350 0.273 0.350 0.230
rs11340646, rs769765211, rs775397699 c.1443‐97del 0.128 Intronic 0.0016 —
rs4646156 c.1071‐605T>A 0.078 Intronic 0.802 0.699 0.803 0.651
rs4646143 c.900 + 1879A>G 0.072 Intronic 0.826 0.727 0.828 0.650
rs397822493 c.187‐1538dup 0.070 Intronic 0.835 0.732
rs111691073 c.1997 + 520_1997 + 527del 0.060 Intronic 0.971 0.940
rs35803318 c.2247G>A 0.060 Coding sequence variant; synonymous 0.020 0.038 0.020 0.050
rs4646152 c.1070 + 1320T>C 0.058 Intronic 0.832 0.729 0.832 0.651
rs879922 c.1542‐361G>C 0.056 Intronic 0.682 0.619 0.682 0.646
rs4240157 c.1897‐1015G>A 0.056 Intronic 0.682 0.617 0.682 0.641
rs397686765, rs398087648, rs4646131, rs869127567 c.345 + 524delT 0.053 Intronic 0.803 0.701
rs233575 c.211‐625C>T 0.051 Intronic 0.863 0.771 0.863 0.664
rs1514279 c.802 + 101C>T 0.048 Intronic 0.803 0.698 0.803 0.646
rs2158083 c.584‐807G>A 0.047 Intronic 0.808 0.703 0.808 0.648
rs2048683 c.584‐920A>C 0.046 Intronic 0.803 0.698 0.803 0.648
rs4646153 c.1071‐1397G>A 0.044 Intronic 0.831 0.730 0.832 0.649
rs2316904 c.901‐1178G>A 0.042 Intronic 0.623 0.827 0.828 0.650
rs146122606, rs57823828, rs754565978 c.346‐1077_346‐1070dupCCTTCCTT 0.041 Intronic NA —
rs776459296, rs759499720, rs752472046 c.584‐8dupA 0.041 Intronic NA — —
rs4646124 c.186 + 2053A>G 0.037 Intronic 0.803 0.699 0.804 0.651
rs1978124 c.186 + 786A>G 0.035 Intronic 0.794 0.625 0.795 0.529
rs4646127 c.187‐2327T>C 0.035 Intronic 0.809 0.692 0.809 0.651
rs138373349, rs4646148 c.901‐380_901‐379insTTAA 0.035 Intronic NA — —
rs11394305 c.901‐1367dup 0.034 Intronic
rs2074192 c.2115‐449G>A 0.033 Intronic 0.363 0.424 0.364 0.426
rs200672831 c.1443‐187G>C 0.032 Intronic NA — —
rs2048684 c.901‐702T>G 0.032 Intronic 0.832 0.729 0.832 0.651
rs11374008 c.1298‐936dup 0.032 Intronic NA — —
rs34481900 c.186 + 2745dup 0.031 Intronic 0.809
rs1514280 c.1897‐499T>C 0.030 Intronic 0.802 0.719 0.802 0.655
rs233574 c.2115‐268A>G 0.029 Intronic 0.842 0.748 0.842 0.670
rs4646120 c.186 + 1113C>T 0.028 Intronic 0.735 0.567 0.735 0.527
rs4646142 c.900 + 534C>G 0.028 Intronic 0.357 0.235 0.359 0.238
rs199544436 c.1443‐168G>C 0.027 Intronic — 0.0001 —
rs2023802 c.187‐1019C>T 0.027 Intronic 0.804 0.702 0.804 0.651
rs4646147 c.901‐1231A>T 0.024 Intronic 0.828 0.724 0.828 0.651
rs2316903 c.901‐1761C>A 0.019 Intronic 0.827 0.724 0.828 0.651
rs2106809 c.186 + 788T>C 0.016 Intronic 0.316 0.191 0.316 0.247
rs41303171 c.2158A>G 0.016 Coding sequence missense variant p. Asn720Asp 0.0045 0.016 0.023 0.018
rs714205 c.2114 + 472G>C 0.015 Intronic 0.308 0.184 0.308 0.205
rs757066 c.583 + 884G>A 0.015 Intronic 0.856 0.750 0.856 0.649
rs892503408 c.1443‐200C>T 0.007 Intronic NA — —
rs1132186 c.2309 + 6768T>G 0.006 Intronic 0.688 0.629 0.688 0.649
rs73195521 c.346‐143A>T 0.006 Intronic 0.0013 0.00303 0.001 0.005
rs73195520 c.439 + 24G>A 0.006 Intronic 0.0013 0.00307 0.001 0.005
rs542683073 c.440‐133G>A 0.005 Intronic — 0.00014 —
‐ c.1297 + 70_1297 + 71insTATGA 0.004 NA — —
rs146598386 c.187‐1124C>A 0.004 Intronic 0.0026 0.01235 0.003 0.009
rs755489152 c.2115‐274del 0.004 Intronic NA — —
rs4830542 c.2309 + 5541G>T 0.004 Intronic 0.684 0.623 0.684 0.649
rs10551988 c.2310‐701_2310‐696del 0.004 Intronic No data
rs780782488 c.584‐19T>A 0.004 Intronic — 0.000223 —
rs34161673 c.697‐161del 0.004 Intronic 0.0019 0.00638 0.002 0.007
rs41297301 c.900 + 90C>A 0.004 Intronic 0.0037 0.01453 0.004 0.012
rs4646188 c.901‐1830T>C 0.004 Intronic 0.0437 0.10405 0.044 0.131
rs1043432251 c.901‐1890del 0.004 Intronic NA — —
rs934301151 c.901‐72C>T 0.004 Intronic — 0.00037 0.00034 —
— c.*812C>A 0.003 NA — —
rs200260858 c.1442 + 90_1442 + 91delCA 0.003 Intronic 0.0074 — 0.007 0.004
— c.186 + 73G>A 0.003 NA — —
— c.186 + 74G>A 0.003 NA — —
— c.186 + 75G>A 0.003 NA — —
— c.186 + 79T>A 0.003 NA — —
rs187959864 c.186 + 80C>A 0.003 Intronic 0.0003 0.00009 0.000264 0.001
rs777042582 c.2114 + 44CAA 0.003 Intronic — 0.00014 0.00013 0.00028
rs4646140 c.802 + 24G>A 0.003 Intronic 0.0601 0.0336 0.060 0.001
rs4646116 c.77A>G 0.003 Coding sequence missense variant p. Lys26Arg 0.002 0.003 0.000 0.010
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3.2. TMPRSS2 gene variant analysis

A total of 13 382 variants from 1072 individuals were analyzed and 490 different variants were detected. Among these variants, 9 were missense and 1 was deletion causing a frameshift. When the variants that have allele frequencies lower than 0.003 were removed, 192 variants remained. Three of those were missense variants, eight were coding sequence synonymous variants, seven were 3′UTR variants, and nine were upstream variants. Details of the 192 variants, calculated allele frequencies in the Turkish population, and global and population‐based allele frequencies obtained from public databases are represented in Table 2.

Table 2.

The list of TMPRSS2 gene variant analysis from the whole‐exome sequencing data (only the variants ≥0.003 are listed)

dbSNP‐ID c.DNA Allele frequency Coding consequence Amino acid change g1000 GnomAD GLOBAL EUR
rs140530035 c.795‐15_795‐14del, c.684‐15_684‐14del 0.449 Intronic 0.81 0.90 0.813 0.977
rs17854725 c.768T>C 0.302 Coding sequence; synonymous variant 0.36 0.47 0.339 0.458
rs422471 c.445 + 14G>A 0.286 Intronic 0.55 0.61 0.555 0.698
rs386416 c.326‐45C>G 0.267 Intronic 0.55 — 0.555 0.700
rs464431 c.1011‐52T>C 0.242 Intronic 0.87 0.96 0.874 0.980
rs112132031 c.1076‐44_1076‐43insCCCGAGGCCTTAG 0.211 Intronic 0.83 — 0.830 0.979
rs75603675 c.−57 + 99G>T, c.23G>T 0.205 Coding sequence; missense_variant p. Gly8Val 0.24 0.36 0.244 0.405
rs462321 c.1172‐115A>G 0.161 Intronic 0.58 0.68 0.578 0.784
rs462326 c.1172‐130C>G 0.135 Intronic 0.57 0.68 0.573 0.784
rs12329760 c.478G>A, c.589G>A 0.129 Coding sequence; missense_variant p. Val197Met 0.26 0.28 0.261 0.236
rs2298659 c.777C>T 0.121 Coding sequence; synonymous variant 0.20 0.25 0.209 0.230
rs458280 c.1011‐144A>C 0.120 Intronic 0.88 0.96 0.879 0.980
rs455922 c.1076‐164A>G 0.112 Intronic 0.88 0.96 0.878 0.981
rs9975014 c.683 + 93T>C 0.106 Intronic 0.26 0.25 0.262 0.254
rs734056 c.572 + 83G>T 0.100 Intronic 0.28 0.37 0.285 0.489
rs458213 c.1011‐54A>T 0.099 Intronic 0.23 0.32 0.225 0.441
rs465576 c.1076‐184G>T 0.094 Intronic 0.83 0.93 0.834 0.979
rs3787950 c.225A>G 0.083 Coding sequence; synonymous variant 0.16 0.11 0.163 0.079
rs9974933 c.683 + 122T>C 0.066 Intronic 0.26 0.25 0.262 0.254
rs429442 c.325 + 102G>A 0.063 Intronic 0.28 0.25 0.280 0.232
rs7364083 c.1011‐149C>T 0.062 Intronic 0.64 0.62 0.639 0.538
rs2838042 c.238 + 176A>G 0.058 Intronic 0.23 0.23 0.233 0.243
rs455281 c.1467 + 589C>A 0.058 Intronic 0.74 0.89 0.736 0.967
rs28524972 c.1076‐101G>C 0.054 Intronic 0.29 — 0.287 0.303
rs2094881 c.795‐288A>G, c.684‐288A>G 0.053 Intronic 0.53 0.63 0.530 0.748
rs4816720 c.445 + 2877G>A 0.053 Intronic 0.82 0.92 0.820 0.977
rs9985159 c.684‐137G>A 0.053 Intronic 0.33 0.33 0.335 0.230
rs386638 c.238 + 1236G>A 0.052 Intronic 0.84 0.95 0.844 0.976
rs2298662 c.727 + 389C>G 0.050 Intronic 0.88 0.96 0.123 0.021
rs365724 c.445 + 1099C>G 0.050 Intronic 0.56 0.62 0.555 0.715
rs112132031, rs71951459 c.1187‐43_1187‐42insCCGAGGCCTTAGT, c.1076‐44_1076‐43insCCCGAGGCCTTAG 0.049 Intronic 0.83 — 0.830 0.979
rs456016 c.1076‐279A>G 0.049 Intronic 0.87 0.96 0.874 0.981
rs4818241 c.445 + 2975T>C 0.048 Intronic 0.87 0.96 0.872 0.978
rs415731 c.126 + 983T>C 0.043 Intronic 0.71 0.70 0.714 0.651
rs2298663 c.727 + 317G>A 0.043 Intronic 0.53 0.62 0.525 0.747
rs417443 c.239‐1658T>C 0.043 Intronic 0.86 — 0.865 0.978
rs457909 c.1467 + 465C>T 0.043 Intronic 0.99 0.99 0.994 —
rs2156300 c.445 + 3565C>T 0.042 Intronic 0.87 0.96 0.872 0.978
rs138365638; rs557282706; rs869112255 c.684‐358_684‐357del, c.573‐358_573‐357del 0.042 Intronic 0.87 0.96 0.874 0.979
rs2156301 c.445 + 3372A>G 0.041 Intronic 0.87 0.96 0.871 0.978
rs402303 c.238 + 1132A>G 0.039 Intronic 0.52 0.58 0.519 0.709
rs4818240 c.445 + 3019A>G 0.038 Intronic 0.82 0.92 0.821 0.977
rs3787947 c.326‐153G>A 0.037 Intronic 0.31 0.34 0.307 0.279
rs467375 c.1075 + 168C>T 0.036 Intronic 0.22 0.32 0.223 0.441
rs7277080 c.−57 + 3608G>A 0.036 Intronic 0.23 0.35 0.230 0.369
rs55964536 c.728‐215G>A 0.035 Intronic 0.24 0.35 0.242 0.483
rs435877 c.−56‐2781C>G 0.033 Intronic 0.81 0.83 0.812 0.852
rs2410430 c.446‐3587T>C 0.033 Intronic 0.87 0.96 0.869 0.978
rs402197 c.445 + 651A>G 0.033 Intronic 0.87 0.96 0.874 0.978
rs462448 c.1172‐407A>G 0.033 Intronic 0.88 0.97 0.879 0.981
rs8131648 c.684‐587A>G 0.033 Intronic 0.56 0.64 0.555 0.744
rs429524 c.‐56‐1825C>G 0.032 Intronic 0.86 0.87 0.860 0.853
rs8131649 c.684‐590A>G 0.032 Intronic 0.56 0.64 0.555 0.746
rs2104810 c.795‐550C>T, c.684‐550C>T 0.031 Intronic 0.53 0.63 0.532 0.745
rs3819138 c.326‐54G>C 0.030 Intronic 0.069 — 0.068 0.151
rs2410429 c.446‐3519T>G 0.029 Intronic 0.62 0.74 0.620 0.744
rs461194 c.1467 + 362G>C 0.029 Intronic 0.87 0.96 0.869 0.969
rs55896064 c.1468‐118C>T 0.029 Intronic 0.078 0.13 0.078 0.133
rs5844077 insA 0.028 Upstream variant 0.78 0.74 0.779 0.730
rs417888 c.239‐1806T>C 0.028 Intronic 0.62 0.62 0.625 0.515
rs73905370 c.1468‐58T>A 0.028 Intronic 0.078 0.13 0.078 0.133
rs456298 c.*1318A>T 0.027 3′UTR variant 0.63 0.72 0.628 0.831
rs462471 c.*1593T>C 0.027 3′UTR variant 0.63 0.74 0.630 0.831
rs35899679 c.239‐1800G>T 0.026 Intronic 0.24 — 0.238 0.463
rs381179 c.445 + 2679A>G 0.026 Intronic — — 0.001 —
rs392370 c.238 + 2117T>G 0.026 Intronic 0.30 0.26 0.302 0.240
rs462574 c.*1340T>C 0.026 3′UTR variant 0.74 0.90 0.743 0.966
rs8126497 c.‐57 + 284C>T 0.026 Intronic 0.10 0.13 0.101 0.199
rs398061769 0.026 Intronic — — 0.555 0.715
rs9974589 c.1171 + 452T>G 0.025 Intronic 0.60 0.60 0.604 0.536
rs383510 c.445 + 1954A>G 0.025 Intronic 0.60 0.57 0.604 0.515
rs415918 c.445 + 445G>A 0.025 intronic 0.56 0.62 0.558 0.713
rs61735794 c.1155G>A, c.1266G>A 0.025 Coding sequence; synonymous variant 0.009 0.02 0.009 0.030
rs2298661 c.728‐219G>T 0.023 Intronic 0.27 0.26 0.268 0.230
rs365025 c.445 + 1254C>G 0.023 Intronic 0.56 0.62 0.559 0.715
rs378616 c.‐57 + 2466G>T 0.023 Intronic 0.71 0.69 0.714 0.717
rs8134203 c.684‐695G>A 0.023 Intronic 0.54 0.63 0.536 0.744
rs375408 c.445 + 717C>T 0.023 Intronic 0.88 0.96 0.877 0.979
rs456142 c.*1573A>G 0.023 3′UTR variant 0.63 0.73 0.630 0.831
rs11701576 c.56‐146T>C 0.022 Intronic 0.16 0.099 0.162 0.106
rs2070788 c.1282 + 587C>T, c.1171 + 587C>T 0.021 Intronic 0.60 0.59 0.603 0.536
rs460976 0.021 Intronic 0.87 0.96 0.872 0.968
rs4290734 c.446‐554T>C 0.020 Intronic 0.24 0.34 0.245 0.487
rs4818239 c.683 + 1024A>G 0.020 Intronic 0.30 0.39 0.302 0.502
rs8134216 c.684‐711G>A 0.020 Intronic 0.54 0.63 0.536 0.745
rs9974995 c.683 + 188G>A 0.020 Intronic 0.26 0.25 0.261 0.253
rs455045 c.126 + 1158G>A 0.020 Intronic 0.63 0.56 0.627 0.493
rs2070787 c.1282 + 446A>C, c.1171 + 446A>C 0.020 Intronic 0.29 — 0.293 0.308
rs34769294 c.238 + 2137dup 0.020 Intronic 0.24 — 0.245 0.238
rs61170417; rs67617179 c.1172‐773_1172‐772del 0.020 Intronic 0.27 0.26 0.266 0.308
rs35041537 c.239‐1849G>A 0.019 Intronic 0.24 0.34 0.240 0.463
rs4283504 0.019 Upstream variant 0.87 0.89 0.874 0.887
rs7279603 c.1172‐759A>G 0.019 Intronic 0.33 0.32 0.334 0.310
rs2298664 c.325 + 253C>G 0.018 Intronic 0.32 — 0.322 0.278
rs2298660 c.728‐210G>A 0.017 Intronic 0.26 0.27 0.259 0.201
rs56097233 c.445 + 1040_445 + 1041del 0.017 Intronic 0.56 0.61 0.555 0.715
rs62217531 c.445 + 2420G>A 0.017 Intronic 0.30 0.39 0.298 0.478
rs430915 c.238 + 1540T>C 0.017 Intronic 0.62 0.62 0.623 0.514
rs7275220 c.238 + 959C>T 0.016 Intronic 0.53 0.66 0.529 0.750
rs139374762; rs75929377 c.557‐671_557‐666delTGTCTG 0.016 Intronic 0.25 0.34 0.253 0.487
rs34624090 c.1075 + 291dup 0.015 Intronic 0.22 0.32 0.224 0.442
rs2070793 c.1282 + 998T>C, c.1171 + 998T>C 0.015 Intronic 0.33 0.32 0.332 0.309
rs57474639 c.1468‐188G>A 0.015 Intronic 0.08 0.14 0.085 0.133
rs8129713 c.‐57 + 3410A>G 0.014 Intronic 0.11 0.13 0.109 0.199
rs386818798 c.1011‐54_1011‐52delACTinsTCC 0.014 Intronic NA — —
rs2070790 c.1282 + 888C>G, c.1171 + 888C>G 0.013 Intronic 0.29 0.29 0.292 0.307
rs2070792 c.1282 + 965C>T, c.1171 + 965C>T 0.013 Intronic 0.33 0.32 0.332 0.309
rs10154090 c.239‐2203A>T 0.013 Intronic 0.30 0.33 0.298 0.273
rs11702475 c.556 + 2753G>A, c.445 + 2753G>A 0.013 Intronic 0.26 0.35 0.259 0.491
rs2298857 c.445 + 2340C>T 0.013 Intronic 0.30 0.26 0.299 0.236
rs915823 c.573‐245T>G 0.013 Intronic 0.16 0.22 0.161 0.204
rs9976780 c.446‐2706G>A 0.013 Intronic 0.56 0.61 0.561 0.723
rs928871 c.239‐1011G>A 0.012 Intronic 0.37 — 0.372 0.279
rs9636988 c.683 + 1054A>G 0.012 Intronic 0.26 0.25 0.261 0.257
rs34783969 c.446‐2109T>A 0.012 Intronic 0.26 0.35 0.257 0.488
rs11088551 0.011 Upstream variant 0.27 0.36 0.246 0.411
rs375760 c.445 + 635C>A 0.011 Intronic 0.22 0.20 0.223 0.232
rs4303795 0.011 Upstream variant 0.25 0.39 0.246 0.411
rs66575656 c.727 + 569G>A 0.011 Intronic 0.25 0.24 0.245 0.257
rs4303794 0.010 Upstream variant 0.25 0.36 0.246 0.411
rs6517669 c.239‐1416T>C 0.010 Intronic 0.37 0.39 0.369 0.278
rs7364088 c.1011‐222C>T 0.010 Intronic 0.30 0.30 0.304 0.263
rs364289 c.445 + 1456C>T 0.010 Intronic 0.30 0.26 0.308 0.224
rs8128074 0.010 Upstream variant 0.87 0.89 0.874 0.886
rs9305744 c.1076‐318C>T 0.010 Intronic 0.31 0.31 0.313 0.233
rs9977234 c.446‐3035C>A 0.010 Intronic 0.20 0.19 0.207 0.232
rs117696554 c.437‐92C>T, c.326‐92C>T 0.009 Intronic 0.008 0.019 0.008 0.028
rs2257202 c.445 + 2606A>G 0.009 Intronic 0.22 0.19 0.217 0.233
rs28548447 c.1011‐330C>T 0.009 Intronic 0.26 0.26 0.264 0.303
rs34983238 c.126 + 1049T>G 0.009 Intronic 0.058 0.08 0.058 0.117
rs61735792 c.300C>T, c.189C>T 0.009 Coding sequence variant; synonymous 0.005 0.009 0.005 0.017
rs73230068 c.1010 + 85C>G 0.009 Intronic 0.013 0.026 0.013 0.039
rs10668560, rs150454800 c.445 + 3305_445 + 3312del 0.009 Intronic NA — —
rs34561135 c.683 + 92C>T 0.009 Intronic 0.017 0.046 0.017 0.053
rs3787946 c.727 + 769C>G 0.009 Intronic 0.28 0.28 0.285 0.231
rs61299115 0.009 Upstream variant 0.25 0.36 0.246 0.411
rs9305745 c.238 + 2209G>A 0.009 Intronic 0.29 0.33 0.292 0.273
rs391099 c.239‐2259A>G 0.008 Intronic 0.30 0.27 0.304 0.240
rs56695953 c.126 + 311C>T 0.008 Intronic 0.12 0.13 0.108 0.200
rs9983252 c.445 + 2999G>C 0.008 Intronic 0.31 0.34 0.313 0.253
rs401371 c.238 + 1471C>G 0.008 Intronic 0.20 0.17 0.196 0.210
rs56066678 c.445 + 3842G>A 0.008 Intronic 0.29 0.26 0.293 0.236
rs743542 c.1425 + 151C>T 0.008 Intronic 0.15 0.10 0.149 0.063
rs918360768 c.239‐480T>C 0.008 Intronic NA — —
rs145283231 c.838 + 1237del. c.727 + 1237del 0.007 Intronic — 0.25 — —
rs2070786 c.1282 + 372A>G. c.1171 + 372A>G 0.007 Intronic 0.30 0.29 0.298 0.308
rs9983330 c.683 + 846T>C 0.007 Intronic 0.26 0.28 0.261 0.235
rs112467088 c.55 + 474T>A, c.‐57 + 605T>A 0.007 Intronic 0.19 0.28 0.186 0.281
rs11911394 c.350‐755A>G 0.007 Intronic 0.37 0.39 0.369 0.279
rs61735793 c.224C>T 0.007 Coding sequence; missense_variant p. Thr75Ile 0.003 0.009 0.003 0.008
rs62217525 c.*221G>A 0.007 3′UTR variant 0.02 0.035 0.021 0.055
rs144192191 c.839‐422_839‐419dup, c.728‐422_728‐419dup 0.007 Intronic 0.28 0.22 0.283 0.263
rs62217527 c.727 + 285G>A 0.007 Intronic 0.046 0.078 0.046 0.117
rs73230088 c.55 + 273G>T 0.007 Intronic 0.08 0.13 0.080 0.157
rs12481984 0.006 Upstream variant 0.24 0.36 0.240 0.406
rs2070789 c.1282 + 771G>A, c.1171 + 771G>A 0.006 Intronic 0.32 0.32 0.315 0.229
rs28360562 c.55 + 1751T>G 0.006 Intronic 0.06 0.08 0.057 0.117
rs34205539 c.‐56‐1430dup 0.006 Intronic 0.06 0.08 0.057 0.117
rs55704664 c.55 + 1266G>A 0.006 Intronic 0.10 0.13 0.057 0.117
rs2838043 c.‐56‐1104G>A 0.006 Intronic 0.11 0.13 0.109 0.200
rs395584 c.‐57 + 3561A>G 0.006 Intronic 0.22 0.11 0.224 0.019
rs55760462 c.127‐1701A>G 0.006 Intronic 0.16 0.24 0.165 0.239
rs61735789 c.540C>T 0.006 Coding sequence variant; synonymous 0.004 0.010 0.004 0.013
rs7283324 c.1172‐364G>A 0.006 Intronic 0.31 0.31 0.312 0.224
rs73372166 c.1467 + 623C>T 0.006 Intronic 0.13 0.18 0.133 0.136
rs2838039 c.445 + 3777A>G 0.005 Intronic 0.31 0.34 0.308 0.254
rs75756279 c.838 + 47G>A 0.005 Intronic 0.004 0.004 0.004 0.008
rs73372163 c.1467 + 669C>T 0.005 Intronic 0.13 0.18 0.132 0.136
rs73905371 c.1467 + 674G>C 0.005 Intronic 0.08 0.14 0.085 0.133
rs3761373 c.56‐406G>A 0.005 Intronic 0.16 0.10 0.163 0.106
rs460751 0.005 Intronic 0.83 0.92 0.826 0.965
rs111220497 c.838 + 1292C>T, c.727 + 1292C>T 0.004 Intronic — 0.31 — —
rs1003030 c.126 + 440T>C 0.004 Intronic 0.16 0.10 0.163 0.106
rs111220481 c.838 + 1319C>G, c.727 + 1319C>G 0.004 Intronic — 0.28 — —
rs143680939 c.*1583del 0.004 3′UTR variant 0.08 — 0.082 0.133
rs201627185 c.557‐2706delG 0.004 Intronic NA — — —
rs2187238 c.‐56‐2635A>G 0.004 Intronic 0.11 0.14 0.112 0.199
rs2838040 c.238 + 1591T>C 0.004 Intronic 0.33 0.36 0.331 0.275
rs28707508 0.004 Upstream variant 0.23 0.34 0.230 0.384
rs34256269 c.126 + 1170C>T 0.004 Intronic 0.08 0.13 0.079 0.159
rs61728255 c.727 + 1468T>C 0.004 Intronic 0.88 0.92 0.880 0.980
rs141788162 c.759C>T 0.003 Coding sequence variant; synonymous 0.002 0.004 0.002 0.003
rs199824558 c.210C>T 0.003 Coding sequence variant; synonymous 0.001 0.0002 0.001 —
rs422761 c.‐56‐877C>T 0.003 Intronic 0.22 0.11 0.225 0.019
rs61459778 c.1468‐343G>C 0.003 Intronic 0.14 0.19 0.136 0.136
rs777860329 0.003 Intronic NA — — —
rs113506821 c.795‐200G>A, c.684‐200G>A 0.003 Intronic 0.02 0.05 0.022 0.050
rs35871560 c.445 + 2741del 0.003 Intronic 0.54 — 0.536 0.680
rs56136037 c.445 + 185C>A 0.003 Intronic 0.014 0.04 0.014 0.046
rs74749793 c.55 + 4225C>A 0.003 Intronic 0.16 0.098 0.158 0.103
rs75200570 c.‐57 + 1396A>G 0.003 Intronic 0.06 0.03 0.056 0.011
rs76000363 c.*1592C>T 0.003 3′UTR variant 0.08 0.14 0.082 0.133
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3.3. In silico findings and functional predictions

The crystal structure of ACE2 (PDB ID: 6LZG) revealed that N‐linked glycan molecules are attached to Asn53, Asn90, and Asn322. 14 Asn90 is a conserved amino acid in a number of bats in which coronaviruses cannot infect through ACE2. Glycosylation of this amino acid regulates the Spike−ACE2 interaction in bats. 15 Glycosylation of Asn90 and its subsequent branching is suggested to decrease the ACE2−Spike binding affinity through steric effects. 16 Lys26 of ACE2 generates critical polar and salt bridge interactions with sugar moiety and nearby amino acids, Glu22 and Asn90 (Figure 1A). To analyze the effect of Lys26Arg mutation we generated in silico mutant on the ACE2−Spike structure using the crystal structure having PDB ID of 6LZG. 14 Since Arg has a larger side chain than Lys, the side chain of Arg cannot fit in the same space. The sterically most favorable orientation of in silico mutation showed that Arg side chain cannot generate polar interactions as in the case of Lys amino acid. Instead, Arg may generate a salt bridge with Asp30 (Figure 1B). Asp30 forms a salt bridge with Lys417 of Spike in the crystal structure (Figure 1). In Lys26Arg mutation, Arg can stabilize the Asp30−Lys417 interaction which may result in higher infectivity of the SARS‐CoV‐2.

Figure 1.

Figure 1

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Structure of ACE2‐Spike (6LZG). (A) ACE2 is shown as a cyan cartoon and Spike is shown on a white surface. At the zoom‐in structure, Lys26 interacting amino acids are shown. (B) In silico generated Lys26Arg ACE2 mutation and its proposed interaction scheme is shown.

The TMPRRS2 has three regions: cytoplasmic, transmembrane, and extracellular. Val160 is found in the extracellular region of the protein. 17 TMPRSS2 structure (PDB ID: 7MEQ) shows that Val160 is located on a beta‐strand structure and surrounded by hydrophobic residues Leu225, Val171, Leu158, and Val149 (Figure 2A). Mutation of Val160 to a less hydrophobic residue may disturb this interaction network. To analyze the effect of Val160Met on TMPRSS2, we mutated valine to methionine in silico. Molecular analysis of Val160Met shows that (i) hydrophobic network cannot be maintained and (ii) there is a steric clash between Met and nearby amino acids for example with Tyr222 which suggests that the mutation may destabilize the protein (Figure 2B). In addition to this analysis, we used DUET server to predict the effect of mutation on the TMPRSS2. 18 DUET uses two previously developed approaches for predictions: knowledge‐based and graph‐based signature methods. All type of calculations in DUET predicts that Val160Met mutation destabilizes the protein (Table 3).

Figure 2.

Figure 2

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Structure of TMPRSS2 (7MEQ). (A) TMPRSS2 is shown as a blue cartoon representation. Val160 and its interacting amino acids are shown. (B) In silico generated Val160Met TMPRSS2 mutation is shown. To show a steric clash between mutant Met160 and a nearby Tyr222, amino acids are shown in red and blue spheres (proportional to their van der Waals radius) (at right).

Table 3.

In silico analysis of TMPRSS2 Val160Met. ∆∆G < 0 indicates destabilization

DUET Results (kcal/mol)
mCSM (∆∆G) −0.847
SDM (∆∆G) −2.39
DUET (∆∆G) −1.251
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4. DISCUSSION

Many studies have demonstrated that the symptoms of COVID‐19 vary greatly among patients. Understanding the reason underlying this heterogeneity in risk of progression to a severe form has been a challenge since the start of the pandemic. There are many known factors that can potentially affect the severity of COVID‐19 infection including greater age, presence of co‐morbidities, smoking, and air pollution. 19 , 20 , 21 In addition to these clinical and environmental factors, genetic variability can also account for the susceptibility to SARS‐CoV‐2 infection and the different clinical presentations observed in COVID‐19 patients. 22 ACE2 and TMPRSS2 are transmembrane surface proteins that play critical roles in viral attachment and host cell entry for SARS‐CoV and SARS‐CoV‐2. SARS‐CoV‐2 binds to ACE2 through the receptor‐binding domain in spike proteins, which are then cleaved by TMPRSS2 to allow fusion with the host cell membrane. 7 , 23 Therefore, polymorphisms in genes encoding these proteins can affect the binding affinity of the viral spike protein to host cells as well as membrane fusion efficiency, modulating the host susceptibility to SARS‐CoV‐2. In this context, we investigated the genetic variability of ACE2 and TMPRSS2 in the Turkish population to show the existence of any enrichment of missense or indel variants in coding regions that may potentially affect the binding dynamics of the virus to host cells and also wanted to compare our results with previous epidemiological studies in different populations.

For both ACE2 and TMPRSS2, majority of variants detected in the Turkish population were intronic. Only 2/70 of ACE2 variants (c.2158A>G;p.Asn720Asp; NM_021804.2 (rs41303171) and c.77A>G;p.Lys26Arg; NM_021804.2 (rs4646116)) (Table 1) and 3/192 of TMPRSS2 variants (c.23G>T;p.Gly8Val; NM_001135099.1 (rs75603675), c.589G>A;p.Val197Met; NM_001135099.1 (rs12329760) and c.224C>T;p.Thr75Ile; NM_005656.3 (rs61735793)) (Table 2) that have allele frequencies above 0.003 were identified as coding variant missense variations.

The most frequent ACE2 variant was identified as rs971249 variant with an allele frequency of 0.581, followed by rs113691336 which has an allele frequency of 0.455 and the third most frequent ACE2 variant was found to be rs4646174 with an allele frequency of 0.404 in the Turkish population. All frequent variants that have allele frequencies above 0.06 were intronic.

Considering the missense variants that potentially affect protein structure or function, ACE2 rs41303171 has a detected allele frequency of 0.016 in the Turkish population. Previous in silico structural analyses have demonstrated that this variation causes ACE2 protein to have a higher binding affinity to TMPRSS2 and may facilitate entry of the virus to the host cells. 24 The global allele frequency of this variant is 0.023, 0.018 in European populations, and 0.001 in the Southern Asian population according to the dbSNP database. The variation was previously mentioned by different groups from Italy, India, and Iran. It was found to be frequent in the study where ACE2 variants in a cohort of SARS‐CoV‐2‐positive Italian patients were investigated. 25 Likely, the variant was reported as a common missense change (AF 0.011) together with rs4646116 and c.631G>A; p.(Gly211Arg) variants in a study conducted with whole‐exome data of 6930 Italian control individuals, which are predicted to affect protein structure and stabilization. 26 c.1051C>G;p.(Leu351Val) and c.1166C>A;p.(Pro389His) were the rare variants detected in this cohort predicted to interfere with the internalization process but were not present in our studied group. In the same study, WES data of 131 patients and 258 controls were compared. The allelic variability in the control group was detected to be statistically significant even though no single variant was significantly enriched between the two groups. c.1166C>A;p.(Pro389His) was one of the missense variants, along with c.1174A>C;p.(Lys392Gln), c.1178C>G;p.(Thr393Ser), and c.1312C>G;p.(Gln438Glu) that was listed as variants leading to an increase in interaction affinity between TMPRSS2 and SARS‐CoV‐2 S protein, where c.1409G>T;p.(Arg470Ile) and c.1247A>G;p.(Tyr416Cys) were found to cause a decrease in a recent study that performed molecular docking analyses. 27 None of these variants were present in the Turkish population included in the present study. In a comprehensive retrospective study, c.1166C>A;p.(Pro389His) was stated to be present only in the Latino/Admixed American population, with an allele frequency of 0.015%. 28

Intronic c.439+4G>A (rs2285666) and c.1888G>C;p.(Asp630His) variants were also detected in the Italian COVID‐19 patient cohort. 25 p.(Asp630His) variant is not present in our study group. However, rs2285666 is the fourth common variant detected in the Turkish population with an allele frequency of 0.326. Allele frequency of the variant in EUR‐TSI (Italy) is 0.186, lower than other populations reported in dbSNP. Additionally, in another study, this variant was found to be the most frequent ACE2 variant detected among clinical exome data of 103 individuals from India. 29 In the same study, the rs4646116 variant was detected in one individual. The variant was shown to potentially affect the binding affinity of SARS‐CoV‐2 spike protein to ACE2 receptor and is not frequent in the Turkish population (0.003) whereas it is not detected in the Italian population according to dbSNP variation data. 30 Consistent with the previous analysis, 31 our in silico model predicts that rs4646116 variation (p. Lys26Arg ACE2) may facilitate the SARS‐CoV‐2 infection via stronger Spike−ACE2 interaction (Figure 1). It was shown to be not associated with COVID‐19 clinical outcomes in Iranian patients. 32 Synonymous exonic c.2247G>A;p.(Val749=) (rs35803318) variant was detected in groups of COVID‐19 patients with different clinical symptoms (mild, severe, and death) in the Iranian population, according to the same study. This variation is relatively common in the Turkish population (AF 0.06) compared to Global (AF 0.02).

p.Arg708Trp, p.Arg710Cys, p.Arg710His, and p.Arg716Cys ACE2 variants that are located in the dimeric interface of ACE2 with TMPRSS2 were found to be present in European, Eastern, Asian, and Latino/Admixed American populations but not present in our Turkish study population in the present study. 28

In a more recent study, in a total of 1378 whole‐exome sequences of individuals from the Middle Eastern populations (Iran, Qatar, and Kuwait), the prevalence of the rs41303171 was noted to be highest among Europeans (2.5%), Iranians (0.6%) when compared to Kuwaitis (0.3%), Qataris (0.2%), and other global populations (0.4%) and minör allele frequency of this variant significantly correlated with the case fatality rates (p < 0.0003) in the corresponding countries as of December 2020. 33 In the same study, they also propose that the rs41303171 variant may enhance TMPRSS2 activation and subsequent viral entry.

Cao et al. investigated allele frequency distributions of 1700 ACE2 variants among different populations. Uneven distribution of some variants between populations was observed in this study. For example, ACE2 rs4646127 intronic variant was shown to be associated with higher expression levels in East‐Asian populations with an allele frequency of 0.993 according to dbSNP data. This variant was also detected in the studied Turkish population with an allele frequency of 0.035.

The most frequent TMPRSS2 variant detected in the Turkish population was the intronic rs140530035 variant with an allele frequency of 0.449. The second most frequent variant is a coding sequence synonymous variant, rs17854725. It has an allele frequency of 0.302. This variant was reported to be rare in the Latin American population and is frequent in the Eastern Asian populations according to the databases. The third most frequent variant in the studied population is the intronic rs422471 variant with the calculated allele frequency of 0.286.

TMPRSS2 rs75603675 and rs12329760 were the missense variants detected in the Turkish population with allele frequencies of 0.205 and 0.129 respectively. Both were within the 10 most frequent variants detected in the studied population. In a recent study, these variants were referred to as variants whose allele frequencies vary by ancestry and geography, differing between East Asians and other populations. 34 Importantly, rs12329760 was predicted to be deleterious by SIFT, PolyPhen‐2, and PROVEAN which suggest altered protein function. Our in silico analyses suggest that the rs12329760 variant (p.Val160Met TMPRSS2) may disrupt the hydrophobic interaction core of TMPRSS2 and destabilize the protein (Figure 2, Table 3). It is in a highly conserved exonic splicing enhancer region of the gene and is strongly associated with TMPRSS2‐ERG fusion translocation in prostate cancer due to the increased risk of exon skipping. 35 Rs75603675, on the other hand, was considered deleterious only by PolyPhen‐2 software. Both could potentially affect the function of TMPRSS2 in facilitating SARS‐CoV‐2 cell entry and therefore may possess a protective role. 36 It was noted in a study that the rs12329760‐T variant allele may have altered the highly conserved scavenger receptor cysteine‐rich (SRCR) domain of TMPRSS2 and also decreased protein stability thus impairing the processing of the spike protein of the SARS‐CoV‐2 A2a subtype. 37 , 38 This may result in the protection of East Asians from the SARS‐CoV‐2 A2a subtype as the variant has a higher allele frequency in that region compared to others and also the Turkish population.

Rs12329760 was reported in 4.85% of individuals studied in India as well. 29 Rs383510, rs2298662, and rs2070788 are three variants, that are known to increase susceptibility to Influenza A (H7N9) and may also affect COVID‐19 infectivity was reported to have low allele frequencies in the Indian population as well as in the Turkish population in our study. 29

A very recent study, which analyzed the association between the rs12329760 and COVID‐19 severity in 2244 critically ill patients with COVID‐19 from the UK intensive care units has shown that the T allele of rs12329760 is associated with a reduced likelihood of developing severe COVID‐19. Results of this study further identified TMPRSS2 protein as a promising drug target, with a potential role for camostat mesylate, which is a drug approved for the treatment of postoperative reflux esophagitis and chronic pancreatitis, in COVID‐19 treatment. 39

In another study among Italian COVID‐19 patients, the rare rs114363287; p.Gly111Arg TMPRSS2 variant was detected with a higher frequency compared to other populations. This variant is missing in our cohort. On the other hand, rs75603675 and rs12329760 which are among frequent TMPRSS2 variants in the general Turkish population were detected in lower frequencies in the COVID‐19 patients, which supports the possible protective role of these two variants against COVID‐19. 40

The other TMPRSS2 missense variant detected in the Turkish population was rs61735793 with an allele frequency of 0.007. The variant has low allele frequencies in all reported populations in the dbSNP database. No studies are associating this variant with COVID‐19 susceptibility or disease severity in any population.

Irham et. al. investigated TMPRSS2 variants affecting expression among populations from different continents. They identified four variants: rs464397, rs469390, rs2070788, and rs383510 that influence TMPRSS2 protein expression in the lungs. 41 Rs464397 and rs469390 variants were not detected in the studied cohort of the Turkish population, whereas rs2070788 and rs383510 were detected with frequencies of 0.021 and 0.025 respectively. These frequencies are lower than other studied populations.

Considering the large population size of Turkey, the sample size may be a limitation in our study. Additionally, we conducted this analysis on the general population. A study with a larger sample size that will include COVID‐19 infected and control groups can be designed for further analysis of alleles affecting susceptibility and disease severity.

5. CONCLUSION

Overall, our data suggests enrichment of the rs4646116 ACE2 functional allele in the Turkish population, which was demonstrated to potentially enhance the binding of the SARS‐CoV‐2 to the receptor by in silico modelling. The two TMPRSS2 missense variants, rs12329760 and rs75603675, that were detected in the Turkish population and have differential frequency distributions in dbSNP may have a role in population‐specific outcomes in COVID‐19 severity. To conclude, new SARS‐CoV‐2 variants and their potentially different transmission abilities, as well as ACE2 and TMPRSS2 gene variants should be considered while developing therapeutics for COVID‐19 disease.

AUTHOR CONTRIBUTIONS

Conceived and designed the analysis: Gulten Tuncel, Mahmut Cerkez Ergoren, Sehime Gulsun Temel. Collected the data: Nilgun Duman, Atil Bisgin, Sevcan Tug Bozdogan, Sebnem Ozemri Sag, Aslihan Kiraz, Burhan Balta, Murat Erdogan, Bulent Uyanik, Sezin Canbek, Pinar Ata, Bilgen Bilge Geckinli, Esra Arslan Ates, Ceren Alavanda, Sevda Yesim Ozdemir, Ozlem Sezer, Gulay Oner Ozgon, Hakan Gurkan, Kubra Guler, Ibrahim Boga, Niyazi Kaya, Adem Alemdar, Murat Sayan, Munis Dundar, Sehime Gulsun Temel. Contributed data or analysis tools: Nilgun Duman, Gulten Tuncel, Atil Bisgin, Sevcan Tug Bozdogan, Sebnem Ozemri Sag, Seref Gul, Aslihan Kiraz, Burhan Balta, Murat Erdogan, Bulent Uyanik, Sezin Canbek, Pinar Ata, Bilgen Bilge Geckinli, Esra Arslan Ates, Ceren Alavanda, Sevda Yesim Ozdemir, Ozlem Sezer, Gulay Oner Ozgon, Hakan Gurkan, Kubra Guler, Ibrahim Boga, Niyazi Kaya, Adem Alemdar, Murat Sayan, Munis Dundar, Mahmut Cerkez Ergoren, Sehime Gulsun Temel. Performed analysis: Nilgun Duman, Gulten Tuncel, Atil Bisgin, Sevcan Tug Bozdogan, Sebnem Ozemri Sag, Seref Gul, Aslihan Kiraz, Burhan Balta, Murat Erdogan, Bulent Uyanik, Sezin Canbek, Pinar Ata, Bilgen Bilge Geckinli, Esra Arslan Ates, Ceren Alavanda, Sevda Yesim Ozdemir, Ozlem Sezer, Gulay Oner Ozgon, Hakan Gurkan, Kubra Guler, Ibrahim Boga, Niyazi Kaya, Adem Alemdar, Murat Sayan, Munis Dundar, Mahmut Cerkez Ergoren, Sehime Gulsun Temel. Wrote the paper: Gulten Tuncel, Seref Gul, Mahmut Cerkez Ergoren, Sehime Gulsun Temel. Read and revised the paper: Nilgun Duman, Gulten Tuncel, Atil Bisgin, Sevcan Tug Bozdogan, Sebnem Ozemri Sag, Seref Gul, Aslihan Kiraz, Burhan Balta, Murat Erdogan, Bulent Uyanik, Sezin Canbek, Pinar Ata, Bilgen Bilge Geckinli, Esra Arslan Ates, Ceren Alavanda, Sevda Yesim Ozdemir, Ozlem Sezer, Gulay Oner Ozgon, Hakan Gurkan, Kubra Guler, Ibrahim Boga, Niyazi Kaya, Adem Alemdar, Murat Sayan, Munis Dundar, Mahmut Cerkez Ergoren, Sehime Gulsun Temel.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

ETHICS STATEMENT

All procedures performed in this study were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards (approval number: YDU/2020/78‐1055).

Supporting information

Supplementary information.

Click here for additional data file. (51.5KB, xlsx)

Supplementary information.

Click here for additional data file. (14.3KB, docx)

Duman N, Tuncel G, Bisgin A, et al. Analysis of ACE2 and TMPRSS2 coding variants as a risk factor for SARS‐CoV‐2 from 946 whole‐exome sequencing data in the Turkish population. J Med Virol. 2022;94:5225‐5243. 10.1002/jmv.27976

Nilgun Duman, Gulten Tuncel, Mahmut Cerkez Ergoren, and Sehime Gulsun Temel contributed equally to this study and should be considered joint first/last authors.

Contributor Information

Mahmut Cerkez Ergoren, Email: mahmutcerkez.ergoren@neu.edu.tr.

Sehime Gulsun Temel, Email: sehime@uludag.edu.tr.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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