Association between single nucleotide polymorphisms (SNPs) of IL1, IL12, IL28 and TLR4 and symptoms of congenital cytomegalovirus infection.

Congenital cytomegalovirus (cCMV) infection is the most common intrauterine infection. A non-specific immune response is the first line of host defense mechanism against human cytomegalovirus (HCMV). There is limited data on associations between Single Nucleotide Polymorphisms (SNPs) in genes involving innate immunity and the risk and clinical manifestation of cCMV infection. The aim of the study was to investigate association between selected SNPs in genes encoding cytokines and cytokine receptors, and predisposition to cCMV infection including symptomatic course of disease and symptoms. A panel of eight SNPs: IL1B rs16944, IL12B rs3212227, IL28B rs12979860, CCL2 rs1024611, DC-SIGN rs735240, TLR2 rs5743708, TLR4 rs4986791, TLR9 rs352140 was analyzed in 233 infants (92 cCMV-infected and 141 healthy controls). Associations between genotyped SNPs and predisposition to cCMV infection and symptoms were analyzed. The association analysis was performed using SNPStats software. No statistically significant association was found between any genotyped SNPs and predisposition to cCMV infection and symptomatic course of disease. In relation to particular symptoms, polymorphism of IL12B rs3212227 was linked to decreased risk of prematurity (OR = 0.37;95%CI,0.14-0.98;p = 0.025), while polymorphism of IL1B rs16944 was linked to reduced risk of splenomegaly (OR = 0.36;95%CI,0.14-0.98; p = 0.034) in infants with cCMV infection. An increased risk of thrombocytopenia was associated with IL28B rs12979860 polymorphism (OR = 2.55;95%CI,1.03-6.32;p = 0.042), while hepatitis was associated with SNP of TLR4rs4986791 (OR = 7.80;95%CI,1.49-40,81; p = 0.024). This is the first study to demonstrate four new associations between SNPs in selected genes (IL1B, IL12B, IL28B, TLR4) and particular symptoms in cCMV disease. Further studies on the role of SNPs in the pathogenesis of cCMV infection and incorporation of selected SNPs in the clinical practice might be considered in the future.

Introduction

Congenital cytomegalovirus (cCMV) infection is the most common intrauterine infection. The HCMV is responsible for approximately 20,000–40,000 congenital infections in the United States each year [1, 2]. Nevertheless, only 10–15% of cCMV-infected newborns present clinical findings after birth, while almost 85–90% are asymptomatic [3]. Both groups are at a high risk of developing long-term sequelae. It concerns about 40–65% of symptomatic and up to 23% of asymptomatic neonates after birth [4, 5].

The clinical manifestations of cCMV disease include intrauterine growth restriction (IUGR), sensorineural hearing loss (SNHL), chorioretinitis and central nervous system (CNS) disorders (microcephaly, seizures, abnormal neuroimaging findings). Hepatobiliary and reticuloendothelial system abnormalities include hepatomegaly, splenomegaly, petechiae, thrombocytopenia, neutropenia, hepatitis and cholestasis. Abnormalities of the hepatobiliary and reticuloendothelial system seem to be transient, while SNHL and CNS disorders tend to be persisted and most devastating to the children [6].

The first line of host defense mechanisms against HCMV is a non-specific (innate) immune response. Single Nucleotide Polymorphisms (SNPs) in genes involving innate immunity has been quite extensively studied in the context of HCMV infections in organ transplant patients and stem cells recipients [7-9]. There is limited data concerning cCMV infection so far. A few previous reports linked SNP polymorphism to the risk of cCMV infection and clinical manifestation of the disease [10-13].

The aim of the study was to investigate association between eight SNPs in candidate genes encoding cytokines and cytokine receptors (IL1B rs16944, IL12B rs3212227, IL28B rs12979860, CCL2 rs1024611, DC-SIGN rs735240, TLR2 rs5743708, TLR4 rs4986791, TLR9 rs352140) and predisposition to cCMV including symptomatic course of the disease and particular symptoms.

Material and methods

Study population

We prospectively enrolled the Caucasian neonates with cCMV (cCMV group) and neonates without cCMV infection (healthy control group) hospitalized in NICU of The Children’s Memorial Health Institute in Warsaw between March 2016 and January 2019.

Inclusion criteria for cCMV group were positive real-time PCR DNA CMV in urine ≤ 21st day of life and parental consent. Exclusion criteria for cCMV group were: multiple congenital anomalies, severe course of bacterial septic disease, other TORCH infections (e.g. congenital toxoplasmosis), lack of parental consent. Inclusion criteria for control group were: negative real-time PCR DNA CMV in urine and parental consent. Exclusion criteria for control group were: positive real-time PCR DNA CMV in urine, multiple congenital syndromes, severe course of bacterial septic disease, other TORCH infections, lack of parental consent.

All neonates with cCMV infection underwent complete physical examination, ophthalmologic and hearing evaluation [newborn hearing screening tests (Otoacoustic Emission, OAE and Auditory Brainstem Response, ABR)]. Additionally, neuroimaging [brain ultrasounds (US) and magnetic resonance imaging (MRI)], and laboratory blood tests (bone marrow function and hepatic parameters) were performed during diagnostic process in NICU.

Patient with symptomatic cCMV infection was defined as newborn who presented at least one of the following HCMV-related signs at birth: microcephaly, abnormal hearing (SNHL was defined as air conduction thresholds > 20dBHL on the ABR with normal bone conduction thresholds and normal middle ear function), chorioretinitis, any neuroimaging findings in MRI (e.g. ventriculomegaly, white matter abnormalities, cerebral cortex defect, peri/intraventricular cyst, intracerebral calcifications, myelin disorders) or at least three abnormalities of hepatobiliary and reticuloendothelial system. Following definitions for laboratory abnormalities were adopted in the study: elevated direct bilirubin >1 mg/dl for cholestasis, elevated level of aspartate transaminase (ASPAT) >84 U/l and/or elevated level of alanine aminotransferase (ALTAT) >60 U/l for hepatitis, thrombocytopenia below 100 K/μl, neutropenia below 1000 K/μl. We did not consider infants with an abnormal muscle tone, seizures, intrauterine growth restriction (IUGR) or prematurity (gestational age <37 weeks) alone as having symptomatic cCMV infection.

Ethics statement

This study protocol was approved by the Ethics Committee of The Children’s Memorial Health Institute on human subjects (28/KBE/2016 and 10/KBE/2017). We obtained written informed consent from parents of each participant before enrollment into the study. We declare compliance with ethical practices in the study.

Detection of HCMV DNA

Total genomic DNA was extracted from 200 μL of clinical specimen (whole blood and urine) using a Nucleosp in Tissue (Macherey-Nagel, Duren, Germany) on QIAcube instrument (Qiagen, Hilden, Germany) with final elution volume of 100 μL according to manufacturer’s instructions. An internal control was included during sample and negative control preparation. The presence of HCMV DNA was evaluated primarily in urine samples. Newborns with cCMV infection had HCMV DNA tested in whole blood. The detection of HCMV DNA was performed by qualitative real-time PCR as described previously [13].

Candidate genes selection

SNPs in eight candidate genes were selected a priori based on previously reported associations in HCMV infections [7, 8, 10, 13–16]. PPRs such as TLR-2 (Toll-like receptor), TLR-4, TLR-9 and DC-SIGN (dendritic cell-specific ICAM-grabbing non-integrin) were chosen due to their role of HCMV recognition and triggering inflammatory cytokines [10, 11, 17–20]. Interleukins such as IL-1B, IL-12B and IL-28B were chosen for their pro-inflammatory and immunomodulatory role in the context of HCMV infection [13, 15, 21, 22]. Finally, we selected CCL 2 (C-C motif chemokine ligand 2) which was a monocyte chemotactic protein–1 (MCP-1) responsible for immune cells differentiation and their migration during inflammation in HCMV infection [23].

Determination of SNP genotypes

SNPs genotyping was performed using genomic DNA extracted from whole blood collected for detection of HCMV. No additional sample of blood from newborn was demanded for the study. Briefly, TaqMan SNP Predesigned Genotyping Assays (Applied Biosystems, Inc., Foster City, CA, USA) were applied for IL1B rs16944, IL12B rs3212227, IL28B rs12979860, CCL2 rs1024611, DC-SIGN rs735240, TLR2 rs5743708, TLR4 rs4986791, TLR9 rs352140 polymorphisms. The allelic discrimination was performed on the 7500 Real-time PCR System (Applied Biosystems) according to the manufacturer’s instructions. A blinded duplicated genotyping of 10 random study samples demonstrated 100% concordance.

Statistical analyses

The normality of the distribution of analyzed data was assessed by Shapiro-Wilk test. Departures from Gaussian distribution were ascertained. Thus, data were presented as median and quartiles and non-parametric Mann-Whitney test was used. Counts were presented as numbers and percentages and Chi squared test was used. In the case of expected number of observations less than 5, Fisher’s exact test was used. The association analysis of eight selected SNPs in following configurations was calculated: cCMV-infected/uninfected, symptomatic/asymptomatic. Among symptomatic infants following symptoms were analyzed: microcephaly, chorioretinitis, abnormal hearing, abnormal MR imaging, hepatomegaly, splenomegaly, petechiae, cholestasis, thrombocytopenia, neutropenia, hepatitis, premature and IUGR. All SNPs were analyzed for Hardy-Weinberg equilibrium (HWE) by using the Chi-square test. The association analysis, including co-dominant, dominant, recessive, over-dominant and log-additive models, was performed using SNPStats software [24]. The Akaike information criteria (AIC) was used to select the best fitted model. The model with the lowest AIC value was the best model. Odds ratios (ORs) with 95% confidence intervals (CIs) for each model were calculated using logistic regression. P- value ≤ 0.05 was considered significant.

Results

Study population characteristics

A total of 233 infants (49.36% males) were enrolled into the study. There were 92 infants with confirmed cCMV infection (cCMV group) and 141 infants with excluded cCMV infection (healthy control group). The maternal and neonatal demographic data and general characteristics of two study groups at admission to Neonatal Department (NICU) are presented in Table 1. Infants with cCMV infection had statistically significant lower birth weight, head circumference, gestational age and younger mothers.

Table 1

Baseline characteristics of the study population including infants with cCMV and healthy control group.

Characteristics	Study population n = 233	cCMV group n = 92	Control group n = 141	P-valueb
Maternal age at delivery, years	29 (26–33)	28(25–31)	29(26–33)	0.004a
Gestational age, weeks	39 (37–40)	38(37–39)	39(38–40)	0.001a
Cesarean section, n (%)	119 (59.17)	49 (54.44)	70 (54.69)	NS
Male, n (%)	115 (49.36)	46 (50.00)	69 (48.94)	NS
Birth weight, g	3080 (2590–3580)	2755 (2170–3200)	3270 (2860–3680)	0.001a
IUGR (<10 percentile), n (%)	42 (18.34)	26 (28.26)	16 (11.68)	0.001a
Head circumference at admission to NICU, cm	35.0 (33.5–36.5)	34.1 (32.0–35.5)	35.5 (34.5–37.0)	0.001a
Length of hospitalization, days	6 (3–10)	8 (5–13)	4 (2–9)	0.001a
Blood tests results:
Thrombocytes, K/μl	346 (214–476)	187 (70–325)	410 (319–501)	0.001a
Neutrophils, K/μl	2352 (1520–3616)	1708 (1255–2676)	3000 (1971–4154)	0.001a
ASPAT, U/l	37 (29–49)	37 (29–52)	37 (30–46)	NS
ALAT, U/l	20 (14–28)	20 (15–31)	21 (14–27)	NS
GGT, U/l	108 (66–186)	123 (64–236)	102 (66–162)	NS
Total bilirubin, mg/dl	4.7 (1.4–8.4)	2.3 (0.9–5.5)	5.8 (2.5–9.3)	0.001a
Direct bilirubin, mg/dl	0.6 (0.5–0.8)	0.6 (0.4–0.9)	0.6 (0.5–0.8)	NS

Data are presented as median (IQR, interquartile range) or number (%).

IUGR, intrauterine growth restriction; cCMV, congenital CMV infection; ASPAT, aspartate aminotransaminase; ALAT, alanine aminotransferase; GGT, Gamma-glutamyl transferase; NS, not significant (p-values above 0.05).

a P-value ≤ 0.05 are statistically significant.

b P-value for comparison between cCMV group and control group.

Newborn infants with confirmed cCMV infection (cCMV group) were symptomatic (n = 73) or asymptomatic (n = 19) at birth (Fig 1).

Fig 1

Description of the study population.

Data are presented as number (n); cCMV–congenital CMV infection. *Cases not enrolled to the study did not meet inclusion criteria due to lack of parental consent.

The clinical manifestation of symptomatic newborns is presented in Table 2. Microcephaly was observed in 23,9% of cases. All newborns with cCMV infection had brain US imaging, followed by brain MRI in over 95% of cases (in less than 5% of cases the MRI imaging was not conducted for technical reasons). Abnormal brain US was noted in 78.26% of cases, while abnormal brain MRI was noted in 86.21% of cases. Abnormalities of reticuloendothelial system such as petechiae, hepato- and splenomegaly occurred in 16.3%, 16.3%, 18.5% of infected newborns, respectively (Table 2).

Table 2

Clinical symptoms and biochemical abnormalities in newborn infants with cCMV infection at diagnosis.

Characteristics	cCMV group n = 92
Central nervous system abnormalities
Microcephaly, n (%)	22 (23.91)
Opisthotonus, n (%)	11 (12.09)
Seizures, n (%)	2 (2.17)
Abnormal muscle tone, n (%)	53 (58.89)
Abnormal ultrasonography imaging, n (%)	72 (78.26)
Abnormal magnetic resonance imaging, n (%)	75 (86.21) (n = 87)
Chorioretinitis, n (%)
Both eyes	8 (8.70)
At least one eye	17 (18.48)
Abnormal OEA, n (%)
Right ear	27 (29.35)
Left ear	31 (33.70)
Both ears	22 (23.91)
At least one ear	36 (39.13)
Abnormal ABR, n (%)
Right ear	21 (25.30) (n = 82)
Left ear	19 (23.45) (n = 81)
Both ears	13 (16.05)
At least one ear	29 (35.80)
Hepatobiliary and reticuloendothelial abnormalities
Petechiae, n (%)	15 (16.30)
Hepatomegaly, n (%)	15 (16.30)
Splenomegaly, n (%)	17 (18.48)
Thrombocytopenia (<100 000 platelets/mm3), n (%)	28 (30.43)
Neutropenia (<1000 neutrophils/μl), n (%)	10 (10.87)
Anemia (relatively to the day of life), n (%)	33 (35.87)
Elevated level of ASPAT (>84 U/l), n (%)	8 (8.79)
Elevated level of ALAT (>60 U/l), n (%)	8 (8.79)
Elevated level of GGT (>203 U/l), n (%)	27 (32.53)
Cholestasis (direct bilirubin >1mg/dl), n (%)	15 (17.44)
Hiperbilirubinemia (total bilirubin >12mg/dl), n (%)	0 (0.00)
Incorrect coagulogram (INR >1.2; APTT >45.0 sec), n (%)	1 (1.18)

Data are presented as number (%).

OAE, Otoemission Acustic; ABR, Auditory Brainstem Response; Aspartate aminotransaminase, ASPAT; ALAT, Alanine aminotransferase; GGTP, Gamma-glutamyltransferase; INR, International Normalized Ratio; APTT, Activated Partial Thromboplastin Time.

Results of SNP genotyping

Eight candidate SNPs were genotyped in 233 infants. All SNPs were in HWE (p>0.05) both in cCMV group and healthy control group.

Associations between SNPs and cCMV infection

Eight selected SNPs were genotyped successfully in all study population. No statistically significant association was found between genotyped SNPs and cCMV infection (Table 3).

Table 3

Associations between eight selected SNPs and cCMV infection.

Gene	dbSNP ID numbera (alleles)	Genetic Model	Genotype	Control Group n = 141	cCMV group n = 92	OR (95% CI)	P-valueb
IL1B	rs16944 (G/A)	Codominant	G/G	71 (50.4)	36 (39.1)	1.00	NS
			A/G	57 (40.4)	49 (53.3)	1.70 (0.97–2.95)
			A/A	13 (9.2)	7 (7.6)	1.06 (0.39–2.89)
		Dominant	G/G	71 (50.4)	36 (39.1)	1.00	NS
			A/G-A/A	70 (49.6)	56 (60.9)	1.58 (0.93–2.69)
		Recessive	G/G-A/G	128 (90.8)	85 (92.4)	1.00	NS
			A/A	13 (9.2)	7 (7.6)	0.81 (0.31–2.12)
		Overdominant	G/G-A/A	84 (59.6)	43 (46.7)	1.00	NS
			A/G	57 (40.4)	49 (53.3)	1.68 (0.99–2.85)
		Log-additive	-	-	-	1.27 (0.84–1.91)	NS
IL12B	rs3212227 (G/T)	Codominant	T/T	82 (58.2)	57 (62)	1.00	NS
			T/G	46 (32.6)	28 (30.4)	0.88 (0.49–1.56)
			G/G	13 (9.2)	7 (7.6)	0.77 (0.29–2.06)
		Dominant	T/T	82 (58.2)	57 (62.0)	1.00	NS
			T/G-G/G	59 (41.8)	35 (38.0)	0.85 (0.50–1.46)
		Recessive	T/T-T/G	128 (90.8)	85 (92.4)	1.00	NS
			G/G	13 (9.2)	7 (7.6)	0.81 (0.31–2.12)
		Overdominant	T/T-G/G	95 (67.4)	64 (69.6)	1.00	NS
			T/G	46 (32.6)	28 (30.4)	0.90 (0.51–1.59)
		Log-additive	-	-	-	0.88 (0.58–1.32)	NS
IL28B	rs12979860 (C/T)	Codominant	C/C	65 (46.1)	41 (44.6)	1.00	NS
			T/C	59 (41.8)	38 (41.3)	1.02 (0.58–1.80)
			T/T	17 (12.1)	13 (14.1)	1.29 (0.53–2.76)
		Dominant	C/C	65 (46.1)	41 (44.6)	1.00	NS
			T/C-T/T	76 (53.9)	51 (55.4)	1.06 (0.63–1.80)
		Recessive	C/C-T/C	124 (87.9)	79 (85.9)	1.00	NS
			T/T	17 (12.1)	13 (14.1)	1.20 (0.55–2.61)
		Overdominant	C/C-T/T	82 (58.2)	54 (58.7)	1.00	NS
			T/C	59 (41.8)	38 (41.3)	0.98 (0.57–1.67)
		Log-additive	-	-	-	1.08 (0.74–1.58)	NS
CCL2	rs1024611 (A/G)	Codominant	A/A	74 (52.5)	50 (54.4)	1.00	NS
			G/A	57 (40.4)	39 (42.4)	1.01 (0.59–1.74)
			G/G	10 (7.1)	3 (3.3)	0.44 (0.12–1.69)
		Dominant	A/A	74 (52.5)	50 (54.4)	1.00	NS
			G/A-G/G	67 (47.5)	42 (45.6)	0.93 (0.55–1.57)
		Recessive	A/A-G/A	131 (92.9)	89 (96.7)	1.00	NS
			G/G	10 (7.1)	3 (3.3)	0.44 (0.12–1.65)
		Overdominant	A/A-G/G	84 (59.6)	53 (57.6)	1.00	NS
			G/A	57 (40.4)	39 (42.4)	1.08 (0.64–1.85)
		Log-additive	-	-	-	0.85 (0.55–1.33)	NS
DC-SIGN	rs735240 (A/G)	Codominant	G/G	53 (37.6)	35 (38.0)	1.00	NS
			G/A	65 (46.1)	37 (40.2)	0.86 (0.48–1.55)
			A/A	23 (16.3)	20 (21.7)	1.32 (0.63–2.75)
		Dominant	G/G	53 (37.6)	35 (38.0)	1.00	NS
			G/A-A/A	88 (62.4)	57 (62.0)	0.98 (0.57–1.69)
		Recessive	G/G-G/A	118 (83.7)	72 (78.3)	1.00	NS
			A/A	23 (16.3)	20 (21.7)	1.43 (0.73–2.78)
		Overdominant	G/G-A/A	76 (53.9)	55 (59.8)	1.00	NS
			G/A	6 (46.1)	37 (40.2)	0.79 (0.46–1.34)
		Log-additive	-	-	-	1.10 (0.77–1.58)	NS
TLR2	rs5743708 (A/G)	-	G/G	126 (89.4)	82 (89.1)	1.00	NS
			G/A	15 (10.6)	10 (10.9)	1.02 (0.44–2.39)
TLR4	rs4986791 (C/T)	Codominant	C/C	126 (89.4)	83 (90.2)	1.00	NS
			T/C	13 (9.2)	9 (9.8)	1.05 (0.43–2.57)
			T/T	2 (1.4)	0 (0.0)	0.00 (0.00-NA)
		Dominant	C/C	126 (89.4)	83 (90.2)	1.00	NS
			T/C-T/T	15 (10.6)	9 (9.8)	0.91 (0.38–2.18)
		Recessive	C/C-T/C	139 (98.6)	92 (100.0)	1.00	NS
			T/T	2 (1.4)	0 (0.0)	0.00 (0.00-NA)
		Overdominant	C/C-T/T	128 (90.8)	83 (90.2)	1.00	NS
			T/C	13 (9.2)	9 (9.8)	1.07 (0.44–2.61)
		Log-additive	-	-	-	0.82 (0.37–1.81)	NS
TLR	rs352140 (C/T)	Codominant	T/T	44 (31.2)	30 (32.6)	1.00	NS
			T/C	74 (52.5)	47 (51.1)	0.93 (0.52–1.68)
			C/C	23 (16.3)	15 (16.3)	0.96 (0.43–2.13)
		Dominant	T/T	44 (31.2)	30 (32.6)	1.00	NS
			T/C-C/C	97 (68.8)	62 (67.4)	0.94 (0.53–1.65)
		Recessive	T/T-T/C	118 (83.7)	77 (83.7)	1.00	NS
			C/C	23 (16.3)	15 (16.3)	1.00 (0.49–2.03)
		Overdominant	T/T-C/C	67 (47.5)	45 (48.9)	1.00	NS
			T/C	74 (52.5)	47 (51.1)	0.95 (0.56–1.60)
		Log-additive	-	-	-	0.97 (0.66–1.43)	NS

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor.

a SNP database (dbSNP) reference number (ID number).

b P-value for comparison between control group and cCMV group.

Associations between SNPs and symptomatic course of cCMV infection

No statistically significant association was discovered between genotyped SNPs and symptomatic course of cCMV infection based on adopted criteria (Table 4).

Table 4

Associations between selected SNPs and symptomatic or asymptomatic course of cCMV infection.

Gene	dbSNP ID numbera (alleles)	Genetic model	Genotype	Asymptomatic n = 19	Symptomatic n = 73	OR (95% CI)	P-valueb
IL1B	rs16944 (G/A)	Codominant	G/G	7 (36.8)	29 (39.7)	1.00	NS
			A/G	10 (52.6)	39 (53.4)	0.94 (0.32–2.77)
			A/A	2 (10.5)	5 (6.8)	0.60 (0.10–3.78)
		Dominant	G/G	7 (36.8)	29 (39.7)	1.00	NS
			A/G-A/A	12 (63.2)	44 (60.3)	0.89 (0.31–2.51)
		Recessive	G/G-A/G	17 (89.5)	68 (93.2)	1.00	NS
			A/A	2 (10.5)	5 (6.8)	0.62 (0.11–3.50)
		Overdominant	G/G-A/A	9 (47.4)	34 (46.6)	1
			A/G	10 (52.6)	39 (53.4)	1.03 (0.38–2.84)	NS
		Log-additive	-	-	-	0.84 (0.37–1.92)	NS
IL12B	rs3212227 (G/T)	Codominant	T/T	14 (73.7)	43 (58.9)	1.0	NS
			T/G	4 (21.1)	24 (32.9)	1.95 (0.58–6.61)
			G/G	1 (5.3)	6 (8.2)	1.95 (0.22–17.65)
		Dominant	T/T	14 (73.7)	43 (58.9)	1.00	NS
			T/G-G/G	5 (26.3)	30 (41.1)	1.95 (0.64–6.00)
		Recessive	T/T-T/G	18 (94.7)	67 (91.8)	1.00	NS
			G/G	1 (5.3)	6 (8.2)	1.61 (0.18–14.26)
		Overdominant	T/T-G/G	15 (79.0)	49 (67.1)	1.00	NS
			T/G	4 (21.1)	24 (32.9)	1.84 (0.55–6.14)
		Log-additive	-	-	-	1.64 (0.66–4.07)	NS
IL28B	rs12979860 (C/T)	Codominant	C/C	11 (57.9)	30 (41.1)	1.00	NS
			T/C	6 (31.6)	32 (43.8)	1.96 (0.64–5.95)
			T/T	2 (10.5)	11 (15.1)	2.02 (0.38–10.58)
		Dominant	C/C	11 (57.9)	30 (41.1)	1.00	NS
			T/C-T/T	8 (42.1)	43 (58.9)	1.97 (0.71–5.48)
		Recessive	C/C-T/C	17 (89.5)	62 (84.9)	1.00	NS
			T/T	2 (10.5)	11 (15.1)	1.51 (0.30–7.46)
		Overdominant	C/C-T/T	13 (68.4)	41 (56.2)	1.0	NS
			T/C	6 (31.6)	32 (43.8)	1.69 (0.58–4.94)
		Log-additive	-	-	-	1.59 (0.73–3.42)	NS
CCL2	rs1024611 (A/G)	Codominant	A/A	10 (52.6)	40 (54.8)	1.00	NS
			G/A	9 (47.4)	30 (41.1)	0.83 (0.30–2.30)
			G/G	0 (0.0)	3 (4.1)	NA (0.00-NA)
		Dominant	A/A	10 (52.6)	40 (54.8)	1.0	NS
			G/A-G/G	9 (47.4)	33 (45.2)	0.92 (0.33–2.52)
		Recessive	A/A-G/A	19 (100.0)	70 (95.9)	1.00	NS
			G/G	0 (0.0)	3 (4.1)	NA (0.00-NA)
		Overdominant	A/A-G/G	10 (52.6)	43 (58.9)	1.00	NS
			G/A	9 (47.4)	30 (41.1)	0.78 (0.28–2.14)
		Log-additive	-	-	-	1.06 (0.43–2.63)	NS
DC-SIGN	rs735240 (A/G)	Codominant	G/G	7 (36.8)	28 (38.4)	1.00	NS
			G/A	6 (31.6)	31 (42.5)	1.29 (0.39–4.31)
			A/A	6 (31.6)	14 (19.2)	0.58 (0.16–2.07)
		Dominant	G/G	7 (36.8)	28 (38.4)	1.00	NS
			G/A-A/A	12 (63.2)	45 (61.6)	0.94 (0.33–2.67)
		Recessive	G/G-G/A	13 (68.4)	59 (80.8)	1.00	NS
			A/A	6 (31.6)	14 (19.2)	0.51 (0.17–1.59)
		Overdominant	G/G-A/A	13 (68.4)	42 (57.5)	1.00	NS
			G/A	6 (31.6)	31 (42.5)	1.60 (0.55–4.68)
		Log-additive	-	-	-	0.79 (0.40–1.53)	NS
TLR2	rs5743708 (A/G)	-	G/G	17 (89.5)	65 (89.0)	1.00	NS
			G/A	2 (10.5)	8 (11.0)	1.05 (0.20–5.39)
TLR4	rs4986791 (C/T)	-	C/C	17 (89.5)	66 (90.4)	1.00	NS
			T/C	2 (10.5)	7 (9.6)	0.90 (0.17–4.74)
TLR9	rs352140 (C/T)	Codominant	T/T	7 (36.8)	23 (31.5)	1.00	NS
			T/C	9 (47.4)	38 (52.0)	1.29 (0.42–3.92)
			C/C	3 (15.8)	12 (16.4)	1.22 (0.27–5.58)
		Dominant	T/T	7 (36.8)	23 (31.5)	1.00	NS
			T/C-C/C	12 (63.2)	50 (68.5)	1.27 (0.44–3.64)
		Recessive	T/T-T/C	16 (84.2)	61 (83.6)	1.00	NS
			C/C	3 (15.8)	12 (16.4)	1.05 (0.26–4.17)
		Overdominant	T/T-C/C	10 (52.6)	35 (48.0)	1.00	NS
			T/C	9 (47.4)	38 (52.0)	1.21 (0.44–3.32)
		Log-additive	-	-	-	1.14 (0.54–2.41)	NS

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor.

a SNP database (dbSNP) reference number (ID number).

b P-value for comparison between asymptomatic and symptomatic infants in cCMV group.

Associations between selected gene SNPs and particular symptoms of cCMV infection

A summary of associations between examined SNPs and symptoms of cCMV infection is shown in Tables 5–8. SNP of IL12B rs3212227 was associated with decreased risk of prematurity (OR = 0.37, 95%CI, 0.14–0.98; p = 0.025) in log-additive model (Table 5). In relation to reticuloendothelial system abnormalities, IL1B rs19944 polymorphism was associated with the reduced risk of splenomegaly (OR = 0.36, 95%CI, 0.14–0.98; p = 0.034) in log-additive model (Table 6). Regarding laboratory blood results, heterozygous T/C genotype of IL28B rs12979860 polymorphism was associated with increased risk of thrombocytopenia (OR = 2.55; 95% CI, 1.03–6.32; p = 0.042) (Table 7), while infants carrying heterozygous T/C genotype at TLR4 rs4986791 had significantly increased risk of hepatitis (OR = 7.80; 95%CI, 1.49–40.81; p = 0.024) (Table 8). We did not find any other associations between examined SNPs and analyzed symptoms of cCMV group (S1–S9 Tables).

Table 5

Associations between SNPs and prematurity in newborn infants with cCMV infection.

Gene	dbSNP ID numbera (alleles)	Genetic Model	Genotype	Term infants n = 69	Pre-term infants n = 23	OR (95% CI)	P-valueb	AIC
IL1B	rs16944 (G/T)	Codominant	G/G	25 (36.2)	11 (47.8)	1.00	0.1	104.9
			A/G	37 (53.6)	12 (52.2)	0.74 (0.28–1.93)
			A/A	7 (10.1)	0 (0.0)	0.00 (0.00-NA)
		Dominant	G/G	25 (36.2)	11 (47.8)	1.00	0.33	106.5
			A/G-A/A	44 (63.8)	12 (52.2)	0.62 (0.24–1.61)
		Recessive	G/G-A/G	62 (89.9)	23 (100.0)	1.00	0.04	103.3
			A/A	7 (10.1)	0 (0.0)	0.00 (0.00-NA)
		Overdominant	G/G-A/A	32 (46.4)	11 (47.8)	1.00	0.9	107.5
			A/G	37 (53.6)	12 (52.2)	0.94 (0.37–2.43)
		Log-additive	-	-	-	0.54 (0.24–1.23)	0.13	105.2
IL12B	rs3212227 (G/T)	Codominant	T/T	39 (56.5)	18 (78.3)	1.00	0.047	103.4
			T/G	23 (33.3)	5 (21.7)	0.47 (0.15–1.44)
			G/G	7 (10.1)	0 (0.0)	0.00 (0.00-NA)
		Dominant	T/T	39 (56.5)	18 (78.3)	1.00	0.056	103.8
			T/G-G/G	30 (43.5)	5 (21.7)	0.36 (0.12–1.08)
		Recessive	T/T-T/G	62 (89.9)	23 (100.0)	1.00	0.040	103.3
			G/G	7 (10.1)	0 (0.0)	0.00 (0.00-NA)
		Overdominant	T/T-G/G	46 (66.7)	18 (78.3)	1.00	0.28	106.3
			T/G	23 (33.3)	5 (21.7)	0.56 (0.18–1.69)
		Log-additive	-	-	-	0.37 (0.14–0.98)	0.025c	102.4
IL28B	rs12979860 (C/T)	Codominant	C/C	32 (46.4)	9 (39.1)	1.00	0.2	106.2
			T/C	30 (43.5)	8 (34.8)	0.95 (0.32–2.78)
			T/T	7 (10.1)	6 (26.1)	3.05 (0.82–11.38)
		Dominant	C/C	32 (46.4)	9 (39.1)	1.00	0.54	107.1
			T/C-T/T	37 (53.6)	14 (60.9)	1.35 (0.51–3.52)
		Recessive	C/C-T/C	62 (89.9)	17 (73.9)	1.00	0.072	104.2
			T/T	7 (10.1)	6 (26.1)	3.13 (0.93–10.54)
		Overdominant	C/C-T/T	39 (56.5)	15 (65.2)	1.00	0.46	106.9
			T/C	30 (43.5)	8 (34.8)	0.69 (0.26–1.85)
		Log-additive	-	-	-	1.58 (0.82–3.07)	0.17	105.6
CCL2	rs1024611 (A/G)	Codominant	A/A	40 (58.0)	10 (43.5)	1.00	0.48	108
			G/A	27 (39.1)	12 (52.2)	1.78 (0.67–4.69)
			G/G	2 (2.9)	1 (4.3)	2.00 (0.16–24.33)
		Dominant	A/A	40 (58.0)	10 (43.5)	1.00	0.23	106
			G/A-G/G	29 (42.0)	13 (56.5)	1.79 (0.69–4.65)
		Recessive	A/A-G/A	67 (97.1)	22 (95.7)	1.00	0.74	107.4
			G/G	2 (2.9)	1 (4.3)	1.52 (0.13–17.62)
		Overdominant	A/A-G/G	42 (60.9)	11 (47.8)	1.00	0.28	106.3
			G/A	27 (39.1)	12 (52.2)	1.70 (0.66–4.39)
		Log-additive	-	-	-	1.64 (0.72–3.74)	0.24	106.1
DC-SIGN	rs735240 (A/G)	Codominant	G/G	25 (36.2)	10 (43.5)	1.00	0.79	109
			G/A	29 (42.0)	8 (34.8)	0.69 (0.24–2.02)
			A/A	15 (21.7)	5 (21.7)	0.83 (0.24–2.91)
		Dominant	G/G	25 (36.2)	10 (43.5)	1.00	0.54	107.1
			G/A-A/A	44 (63.8)	13 (56.5)	0.74 (0.28–1.93)
		Recessive	G/G-G/A	54 (78.3)	18 (78.3)	1.00	1	107.5
			A/A	15 (21.7)	5 (21.7)	1.00 (0.32–3.14)
		Overdominant	G/G-A/A	40 (58.0)	15 (65.2)	1.00	0.54	107.1
			G/A	29 (42.0)	8 (34.8)	0.74 (0.28–1.96)
		Log-additive	-	-	-	0.88 (0.47–1.65)	0.69	107.3
TLR2	rs5743708 (A/G)	-	G/G	60 (87.0)	22 (95.7)	1.00	0.21	105.9
			G/A	9 (13.0)	1 (4.3)	0.30 (0.04–2.53)
TLR4	rs4986791 (C/T)	-	C/C	64 (92.8)	19 (82.6)	1.00	0.18	105.7
			T/C	5 (7.2)	4 (17.4)	2.69 (0.66–11.05)
TLR9	rs352140 (C/T)	Codominant	T/T	26 (37.7)	4 (17.4)	1.00	0.17	105.9
			T/C	33 (47.8)	14 (60.9)	2.76 (0.81–9.38)
			C/C	10 (14.5)	5 (21.7)	3.25 (0.72–14.62)
		Dominant	T/T	26 (37.7)	4 (17.4)	1.00	0.062	104
			T/C-C/C	43 (62.3)	19 (82.6)	2.87 (0.88–9.38)
		Recessive	T/T-T/C	59 (85.5)	18 (78.3)	1.00	0.43	106.8
			C/C	10 (14.5)	5 (21.7)	1.64 (0.50–5.42)
		Overdominant	T/T-C/C	36 (52.2)	9 (39.1)	1.00	0.28	106.3
			T/C	33 (47.8)	14 (60.9)	1.70 (0.65–4.44)
		Log-additive	-	-	-	1.82 (0.90–3.70)	0.093	104.6

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; AIC, Akaike information criterion; p-values below 0.05 are statistically significant; IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor.

a SNP database (dbSNP) reference number (ID number).

b P-value for comparison between term infants and pre-term infants in cCMV group.

c The best fitted model based on AIC.

Table 8

Associations between SNPs and hepatitis in newborn infants with cCMV infection.

Gene	dbSNP IDnumbera	Genetic Model	Genotype	Without hepatitis n = 84	With hepatitis n = 8	OR (95% CI)	P-valueb	AIC
IL1B	rs16944 (G/A)	Codominant	G/G	32 (38.1)	4 (50.0)	1.00	0.46	58.8
			A/G	45 (53.6)	4 (50.0)	0.71 (0.17–3.06)
			A/A	7 (8.3)	0 (0.0)	0.00 (0.00-NA)
		Dominant	G/G	32 (38.1)	4 (50.0)	1.00	0.51	57.9
			A/G-A/A	52 (61.9)	4 (50.0)	0.62 (0.14–2.63)
		Recessive	G/G-A/G	77 (91.7)	8 (100.0)	1.00	0.25	57
			A/A	7 (8.3)	0 (0.0)	0.00 (0.00-NA)
		Overdominant	G/G-A/A	39 (46.4)	4 (50.0)	1.00	0.85	58.3
			A/G	45 (53.6)	4 (50.0)	0.87 (0.20–3.70)
		Log-additive	-	-	-	0.56 (0.16–2.00)	0.36	57.5
IL12B	rs3212227 (G/T)	Codominant	T/T	51 (60.7)	6 (75.0)	1.00	0.45	58.8
			T/G	26 (30.9)	2 (25.0)	0.65 (0.12–3.47)
			G/G	7 (8.3)	0 (0.0)	0.00 (0.00-NA)
		Dominant	T/T	51 (60.7)	6 (75.0)	1.00	0.41	57.7
			T/G-G/G	33 (39.3)	2 (25.0)	0.52 (0.10–2.71)
		Recessive	T/T-T/G	77 (91.7)	8 (100.0)	1.00	0.25	57
			G/G	7 (8.3)	0 (0.0)	0.00 (0.00-NA)
		Overdominant	T/T-G/G	58 (69)	6 (75.0)	1.00	0.72	58.2
			T/G	26 (30.9)	2 (25.0)	0.74 (0.14–3.93)
		Log-additive	-	-	-	0.49 (0.11–2.14)	0.3	57.3
IL28B	rs12979860 (C/T)	Codominant	C/C	40 (47.6)	1 (12.5)	1.00	0.093	55.6
			T/C	32 (38.1)	6 (75)	7.50 (0.86–65.52)
			T/T	12 (14.3)	1 (12.5)	3.33 (0.19–57.39)
		Dominant	C/C	40 (47.6)	1 (12.5)	1.00	0.041	54.2
			T/C-T/T	44 (52.4)	7 (87.5)	6.36 (0.75–54.01)
		Recessive	C/C-T/C	72 (85.7)	7 (87.5)	1.00	0.89	58.3
			T/T	12 (14.3)	1 (12.5)	0.86 (0.10–7.60)
		Overdominant	C/C-T/T	52 (61.9)	2 (25)	1.00	0.043	54.3
			T/C	32 (38.1)	6 (75)	4.87 (0.93–25.63)
		Log-additive	-	-	-	1.89 (0.70–5.13)	0.21	56.8
CCL2	rs1024611 (A/G)	Codominant	A/A	48 (57.1)	2 (25)	1.00	0.14	56.5
			G/A	34 (40.5)	5 (62.5)	3.53 (0.65–19.28)
			G/G	2 (2.4)	1 (12.5)	12.00 (0.74–194.64)
		Dominant	A/A	48 (57.1)	2 (25)	1.00	0.078	55.2
			G/A-G/G	36 (42.9)	6 (75)	4.00 (0.76–20.99)
		Recessive	A/A-G/A	82 (97.6)	7 (87.5)	1.00	0.22	56.9
			G/G	2 (2.4)	1 (12.5)	5.86 (0.47–72.91)
		Overdominant	A/A-G/G	50 (59.5)	3 (37.5)	1.00	0.23	56.9
			G/A	34 (40.5)	5 (62.5)	2.45 (0.55–10.94)
		Log-additive	-	-	-	3.49 (0.98–12.44)	0.049	54.5
DC-SIGN	rs735240 (A/G)	Codominant	G/G	33 (39.3)	2 (25.0)	1.00	0.71	59.7
			G/A	33 (39.3)	4 (50.0)	2.00 (0.34–11.68)
			A/A	18 (21.4)	2 (25.0)	1.83 (0.24–14.13)
		Dominant	G/G	33 (39.3)	2 (25.0)	1.00	0.41	57.7
			G/A-A/A	51 (60.7)	6 (75.0)	1.94 (0.37–10.20)
		Recessive	G/G-G/A	66 (78.6)	6 (75.0)	1.00	0.82	58.3
			A/A	18 (21.4)	2 (25.0)	1.22 (0.23–6.58)
		Overdominant	G/G-A/A	51 (60.7)	4 (50.0)	1.00	0.56	58
			G/A	33 (39.3)	4 (50.0)	1.55 (0.36–6.61)
		Log-additive	-	-	-	1.36 (0.53–3.51)	0.53	58
TLR2	rs5743708 (A/G)	-	G/G	75 (89.3)	7 (87.5)	1.00	0.88	58.3
			G/A	9 (10.7)	1 (12.5)	1.19 (0.13–10.81)
TLR4	rs4986791 (C/T)	-	C/C	78 (92.9)	5 (62.5)	1.00	0.024c	53.2
			T/C	6 (7.1)	3 (37.5)	7.80 (1.49–40.81)
TLR9	rs352140 (C/T)	Codominant	T/T	27 (32.1)	3 (37.5)	1.00	0.22	57.4
			T/C	42 (50.0)	5 (62.5)	1.07 (0.24–4.85)
			C/C	15 (17.9)	0 (0.0)	0.00 (0.00-NA)
		Dominant	T/T	27 (32.1)	3 (37.5)	1.00	0.76	58.3
			T/C-C/C	57 (67.9)	5 (62.5)	0.79 (0.18–3.55)
		Recessive	T/T-T/C	69 (82.1)	8 (100.0)	1.00	0.084	55.4
			C/C	15 (17.9)	0 (0.0)	0.00 (0.00-NA)
		Overdominant	T/T-C/C	42 (50.0)	3 (37.5)	1.00	0.5	57.9
			T/C	42 (50%)	5 (62.5)	1.67 (0.37–7.42)
		Log-additive	-	-	-	0.59 (0.19–1.83)	0.35	57.5

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; AIC, Akaike information criterion; p-values below 0.05 are statistically significant; IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor.

a SNP database (dbSNP) reference number (ID number).

b P-value for comparison between infants without hepatitis and with hepatitis in cCMV group.

c The best fitted model based on AIC.

Table 6

Associations between SNPs and splenomegaly in newborn infants with cCMV infection.

Gene	dbSNP ID numbera (alleles)	Genetic Model	Genotype	Without splenomegaly n = 75	With splenomegaly n = 17	OR (95% CI)	P-valueb	AIC
IL1B	rs16944 (G/A)	Codominant	G/G	26 (34.7)	10 (58.8)	1.00	0.07	88.7
			A/G	42 (56.0)	7 (41.2)	0.43 (0.15–1.28)
			A/A	7 (9.3)	0 (0.0)	0.00 (0.00-NA)
		Dominant	G/G	26 (34.7)	10 (58.8)	1.00	0.068	88.7
			A/G-A/A	49 (65.3)	7 (41.2)	0.37 (0.13–1.09)
		Recessive	G/G-A/G	68 (90.7)	17 (100.0)	1.00	0.084	89.1
			A/A	7 (9.3)	0 (0.0)	0.00 (0.00-NA)
		Overdominant	G/G-A/A	33 (44.0)	10 (58.8)	1.00	0.27	90.8
			A/G	42 (56.0)	7 (41.2)	0.55 (0.19–1.60)
		Log-additive	-	-	-	0.36 (0.14–0.98)	0.034c	87.6
IL12B	rs3212227 (G/T)	Codominant	T/T	45 (60.0)	12 (70.6)	1.00	0.21	90.9
			T/G	23 (30.7)	5 (29.4)	0.82 (0.26–2.60)
			G/G	7 (9.3)	0 (0.0)	0.00 (0.00-NA)
		Dominant	T/T	45 (60.0)	12 (70.6)	1.00	0.41	91.4
			T/G-G/G	30 (40.0)	5 (29.4)	0.62 (0.20–1.96)
		Recessive	T/T-T/G	68 (90.7)	17 (100.0)	1.00	0.084	89.1
			G/G	7 (9.3)	0 (0.0)	0.00 (0.00-NA)
		Overdominant	T/T-G/G	52 (69.3)	12 (70.6)	1.00	0.92	92
			T/G	23 (30.7)	5 (29.4)	0.94 (0.30–2.98)
		Log-additive	-	-	-	0.56 (0.21–1.49)	0.22	90.6
IL28B	rs12979860 (C/T)	Codominant	C/C	34 (45.3)	7 (41.2)	1.00	0.86	93.8
			T/C	30 (40.0)	8 (47.1)	1.30 (0.42–4.00)
			T/T	11 (14.7)	2 (11.8)	0.88 (0.16–4.89)
		Dominant	C/C	34 (45.3)	7 (41.2)	1.00	0.76	92
			T/C-T/T	41 (54.7)	10 (58.8)	1.18 (0.41–3.45)
		Recessive	C/C-T/C	64 (85.3)	15 (88.2)	1.00	0.75	92
			T/T	11 (14.7)	2 (11.8)	0.78 (0.16–3.87)
		Overdominant	C/C-T/T	45 (60.0)	9 (52.9)	1.00	0.6	91.8
			T/C	30 (40.0)	8 (47.1)	1.33 (0.46–3.84)
		Log-additive	-	-	-	1.03 (0.49–2.16)	0.95	92.1
CCL2	rs1024611 (A/G)	Codominant	A/A	41 (54.7)	9 (52.9)	1.00	0.82	93.7
			G/A	32 (42.7)	7 (41.2)	1.00 (0.33–2.97)
			G/G	2 (2.7)	1 (5.9)	2.28 (0.19–27.93)
		Dominant	A/A	41 (54.7)	9 (52.9)	1.00	0.9	92
			G/A-G/G	34 (45.3)	8 (47.1)	1.07 (0.37–3.08)
		Recessive	A/A-G/A	73 (97.3)	16 (94.1)	1.00	0.53	91.7
			G/G	2 (2.7)	1 (5.9)	2.28 (0.19–26.72)
		Overdominant	A/A-G/G	43 (57.3)	10 (58.8)	1.00	0.91	92
			G/A	32 (42.7)	7 (41.2)	0.94 (0.32–2.74)
		Log-additive	-	-	-	1.17 (0.46–2.94)	0.74	92
DC-SIGN	rs735240 (A/G)	Codominant	G/G	30 (40.0)	5 (29.4)	1.00	0.71	93.4
			G/A	29 (38.7)	8 (47.1)	1.66 (0.48–5.65)
			A/A	16 (21.3)	4 (23.5)	1.50 (0.35–6.38)
		Dominant	G/G	30 (40.0)	5 (29.4)	1.00	0.41	91.4
			G/A-A/A	45 (60.0)	12 (70.6)	1.60 (0.51–5.01)
		Recessive	G/G-G/A	59 (78.7)	13 (76.5)	1.00	0.84	92
			A/A	16 (21.3)	4 (23.5)	1.13 (0.33–3.96)
		Overdominant	G/G-A/A	46 (61.3)	9 (52.9)	1.00	0.53	91.7
			G/A	29 (38.7)	8 (47.1)	1.41 (0.49–4.07)
		Log-additive	-	-	-	1.25 (0.63–2.49)	0.53	91.7
TLR2	rs5743708 (A/G)	-	G/G	67 (89.3)	15 (88.2)	1.00	0.9	92
			G/A	8 (10.7)	2 (11.8)	1.12 (0.21–5.80)
TLR4	rs4986791 (C/T)	-	C/C	70 (93.3)	13 (76.5)	1.00	0.056	88.4
			T/C	5 (6.7)	4 (23.5)	4.31 (1.02–18.22)
TLR9	rs352140 (C/T)	Codominant	T/T	24 (32.0)	6 (35.3)	1.00	0.93	93.9
			T/C	39 (52.0)	8 (47.1)	0.82 (0.25–2.66)
			C/C	12 (16.0)	3 (17.6)	1.00 (0.21–4.71)
		Dominant	T/T	24 (32.0)	6 (35.3)	1.00	0.79	92
			T/C-C/C	51 (68.0)	11 (64.7)	0.86 (0.29–2.61)
		Recessive	T/T-T/C	63 (84.0)	14 (82.3)	1.00	0.87	92
			C/C	12 (16.0)	3 (17.6)	1.13 (0.28–4.52)
		Overdominant	T/T-C/C	36 (48.0)	9 (52.9)	1.00	0.71	91.9
			T/C	39 (52.0)	8 (47.1)	0.82 (0.29–2.36)
		Log-additive	-	-	-	0.96 (0.44–2.10)	0.93	92

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; AIC, Akaike information criterion; p-values below 0.05 are statistically significant; IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor.

a SNP database (dbSNP) reference number (ID number).

b P-value for comparison between infants without splenomegaly and with splenomegaly in cCMV group.

c The best fitted model based on AIC.

Table 7

Associations between SNPs and thrombocytopenia in newborn infants with cCMV infection.

Gene	dbSNP ID numbera	Genetic Model	Genotype	Without thrombocytopenia n = 64	With thrombocytopenia n = 28	OR (95% CI)	P-valueb	AIC
IL1B	rs16944 (G/A)	Codominant	G/G	24 (37.5)	12 (42.9)	1.00	0.57	117.9
			A/G	34 (53.1)	15 (53.6)	0.88 (0.35–2.22)
			A/A	6 (9.4)	1 (3.6)	0.33 (0.04–3.09)
		Dominant	G/G	24 (37.5)	12 (42.9)	1.00	0.63	116.8
			A/G-A/A	40 (62.5)	16 (57.1)	0.80 (0.32–1.97)
		Recessive	G/G-A/G	58 (90.6)	27 (96.4)	1.00	0.3	116
			A/A	6 (9.4)	1 (3.6)	0.36 (0.04–3.12)
		Overdominant	G/G-A/A	30 (46.9)	13 (46.4)	1.00	0.97	117.1
			A/G	34 (53.1)	15 (53.6)	1.02 (0.42–2.48)
		Log-additive	-	-	-	0.73 (0.35–1.55)	0.41	116.4
IL12B	rs3212227 (G/T)	Codominant	T/T	37 (57.8)	20 (71.4)	1.00	0.37	117.1
			T/G	21 (32.8)	7 (25)	0.62 (0.22–1.70)
			G/G	6 (9.4)	1 (3.6)	0.31 (0.03–2.74)
		Dominant	T/T	37 (57.8)	20 (71.4)	1.00	0.21	115.5
			T/G-G/G	27 (42.2)	8 (28.6)	0.55 (0.21–1.43)
		Recessive	T/T-T/G	58 (90.6)	27 (96.4)	1.00	0.3	116
			G/G	6 (9.4)	1 (3.6)	0.36 (0.04–3.12)
		Overdominant	T/T-G/G	43 (67.2)	21 (75.0)	1.00	0.45	116.5
			T/G	21 (32.8)	7 (25.0)	0.68 (0.25–1.86)
		Log-additive	-	-	-	0.59 (0.27–1.28)	0.16	115.1
IL28B	rs12979860 (C/T)	Codominant	C/C	31 (48.4)	10 (35.7)	1.0	0.099	114.4
			T/C	22 (34.4)	16 (57.1)	2.25 (0.86–5.89)
			T/T	11 (17.2)	2 (7.1)	0.56 (0.11–2.98)
		Dominant	C/C	31 (48.4)	10 (35.7)	1.0	0.26	115.8
			T/C-T/T	33 (51.6)	18 (64.3)	1.69 (0.68–4.22)
		Recessive	C/C-T/C	53 (82.8)	26 (92.9)	1.0	0.18	115.3
			T/T	11 (17.2)	2(7.1)	0.37 (0.08–1.80)
		Overdominant	C/C-T/T	42 (65.6)	12 (42.9)	1.00	0.042c	112.9
			T/C	22 (34.4)	16 (57.1)	2.55 (1.03–6.32)
		Log-additive	-	-	-	1.06 (0.56–1.98)	0.87	117
CCL2	rs1024611 (A/G)	Codominant	A/A	35 (54.7)	15 (53.6)	1.00	0.99	119.1
			G/A	27 (42.2)	12 (42.9)	1.04 (0.42–2.58)
			G/G	2 (3.1)	1 (3.6)	1.17 (0.10–13.87)
		Dominant	A/A	35 (54.7)	15 (53.6)	1.00	0.92	117.1
			G/A-G/G	29 (45.3)	13 (46.4)	1.05 (0.43–2.55)
		Recessive	A/A-G/A	62 (96.9)	27 (96.4)	1.00	0.91	117.1
			G/G	2 (3.1)	1 (3.6)	1.15 (0.10–13.21)
		Overdominant	A/A-G/G	37 (57.8)	16 (57.1)	1.00	0.95	117.1
			G/A	27 (42.2)	12 (42.9)	1.03 (0.42–2.52)
		Log-additive	-	-	-	1.05 (0.48–2.31)	0.9	117.1
DC-SIGN	rs735240 (A/G)	Codominant	G/G	24 (37.5)	11 (39.3)	1.00	0.99	119
			G/A	26 (40.6)	11 (39.3)	0.92 (0.34–2.52)
			A/A	14 (21.9)	6 (21.4)	0.94 (0.28–3.08)
		Dominant	G/G	24 (37.5)	11 (39.3)	1.00	0.87	117
			G/A-A/A	40 (62.5)	17 (60.7)	0.93 (0.37–2.31)
		Recessive	G/G-G/A	50 (78.1)	22 (78.6)	1.00	0.96	117.1
			A/A	14 (21.9)	6 (21.4)	0.97 (0.33–2.87)
		Overdominant	G/G-A/A	38 (59.4)	17 (60.7)	1.00	0.9	117.1
			G/A	26 (40.6)	11 (39.3)	0.95 (0.38–2.34)
		Log-additive	-	-	-	0.96 (0.53–1.73)	0.9	117.1
TLR2	rs5743708 (A/G)	-	G/G	58 (90.6)	24 (85.7)	1.00	0.5	116.6
			G/A	6 (9.4)	4 (14.3)	1.61 (0.42–6.23)
TLR4	rs4986791 (C/T)	-	C/C	59 (92.2)	24 (85.7)	1.00	0.35	116.2
			T/C	5 (7.8)	4 (14.3)	1.97 (0.49–7.96)
TLR9	rs352140 (C/T)	Codominant	T/T	19 (29.7)	11 (39.3)	1.00	0.5	117.7
			T/C	33 (51.6)	14 (50)	0.73 (0.28–1.93)
			C/C	12 (18.8)	3 (10.7)	0.43 (0.10–1.87)
		Dominant	T/T	19 (29.7)	11 (39.3)	1.00	0.37	116.3
			T/C-C/C	45 (70.3)	17 (60.7)	0.65 (0.26–1.65)
		Recessive	T/T-T/C	52 (81.2)	25 (89.3)	1.00	0.32	116.1
			C/C	12 (18.8)	3 (10.7)	0.52 (0.13–2.01)
		Overdominant	T/T-C/C	31 (48.4)	14 (50.0)	1.00	0.89	117
			T/C	33 (51.6)	14 (50.0)	0.94 (0.39–2.28)
		Log-additive	-	-	-	0.68 (0.35–1.33)	0.25	115.7

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; AIC, Akaike information criterion; p-values below 0.05 are statistically significant; IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor.

a SNP database (dbSNP) reference number (ID number).

b P-value for comparison between infants without thrombocytopenia and with thrombocytopenia in cCMV group.

c The best fitted model based on AIC.

Discussion

This is the first report on the relation between eights elected SNPs in genes encoding cytokines and cytokine receptors (IL1B rs16944, IL12B rs3212227, IL28B rs12979860, CCL2 rs1024611, DC-SIGN rs735240, TLR2rs5743708, TLR4 rs4986791, TLR9 rs352140), and the risk of cCMV infection and symptoms of the disease in the Caucasian newborns with cCMV infection. We found no association between analyzed SNPs and cCMV infection or symptomatic course of disease. However, our previous study documented, that rare T/T genotype of IL1B rs16944 polymorphism was linked to over two-fold higher risk of cCMV infection [13]. High IL-1β level was suggested to provoke an activation of Th1 (T-helper) cells and inflammatory response [25]. We speculate that the lower sample size of the control group in the current study might explain different results [13]. Interestingly, Wujcicka et al found that heterozygotous C/T genotype of IL1A -899 polymorphism increased the risk of cCMV infection and development of symptomatic infection [22]. Moreover, some SNPs of Toll-like receptors (TLRs) were suggested to promote cCMV infection. It was reported that heterozygotous G/A genotype of TLR9 rs352140 polymorphism increased the risk of cCMV infection by 4.81 times, while heterozygotous G/A genotype of TLR2 rs5743708 polymorphism increased that risk by 10 times. However, we could not replicate these findings in our study. This discrepancy could be because of differences in the study population (due to different enrollment criteria). In addition, both previous studies were performed on merely about twenty cCMV-infected cases and similar number of cases of control group [10, 19].

To the best of our knowledge, there is limited data on associations between SNPs and particular symptoms in cCMV infection so far. Unexpectedly, we found no association between selected SNPs and CNS abnormalities or hearing loss in present study. Although, association between polymorphism of CCL2 rs1024611 and SNHL was previously demonstrated in a larger cohort [13]. Nevertheless, current study turned out to be the first one which proved novel associations between examined SNPs and particular symptoms involving hepatobiliary and reticuloendothelial system disorders and prematurity. Firstly, we observed a relation between decreased risk of prematurity and SNP polymorphism of IL12B rs3212227 in newborn infants with cCMV infection. It is well known that herpes virus infection may result in pregnancy complications such as preterm birth [26]. Furthermore, CMV infection in preterm infants may promote more complications such as bronchopulmonary dysplasia (BPD) in comparison to term infants [27-31]. However, prematurity is not a pathognomonic symptom for cCMV infection. Considering limited data, this study was the first one that showed the link between IL12B rs3212227 polymorphism and reduced risk o prematurity in cCMV-infected patients. IL-12 is an inflammatory cytokine that may influence on Th1 cells, which take part in host immune defense against infection. So far, a number of previous studies have reported associations of IL-12 polymorphisms and other infectious diseases. It was hypothesized that IL12Brs3212227 polymorphism might reduce risk of invasive aspergillosis among immunocompromised patients due to alternative splicing of IL12B mRNA and altering mRNA expression which in turn, might dysregulate IL12-mediated Th1 cells response [32]. The polymorphisms in IL12 gene were also proved to support host's defense against HCV infection through more efficient response to antiviral therapy. However, not only protective role of IL12B rs3212227 was previously observed. Some reports documented that several SNPs of IL12 increased the risk of autoimmune diseases [33, 34]. Certainly, further investigations are needed to confirm the relationship between IL12B rs3212227 polymorphism and the decreased risk of prematurity and evaluate the pathomechanism of its action.

Next, we observed the association between polymorphism of IL1B rs16944 and the reduced risk of splenomegaly. Previously, there were some attempts to find out if splenomegaly is associated with SNPs in other diseases, but none of examined polymorphism predicted splenomegaly development [35]. The spleen, the lymphoid organ and reservoir of myeloid cells, was proved to mobilize neutrophils and inflammatory monocytes/macrophages to the blood when affected by the presence of IL-1β in multiple sclerosis [36]. Additionally, the expression of IL1B mRNA was detected in the spleen [37]. Until now, IL-1β polymorphisms were linked to some other diseases, including pediatric Helicobacter pylori infection, septic shock and seasonal influenza A/H3N2 virus infection [38].

In our study, 88% patients with splenomegaly demonstrated severe thrombocytopenia. We found that infants carrying heterozygous T/C genotype of IL28B rs12979860 polymorphism demonstrated a significantly higher frequency of thrombocytopenia in comparison to C/C-T/T genotypes. It should be underlined that, this is the first report to connect SNP of IL28B rs12979860 and increased risk of thrombocytopenia in cCMV infection. On the other hand, Thomas et al. documented that C/C genotype of IL28B rs12979860 was a predictor of virus elimination in patients with HCV infection [39]. By contrast, protective effect of the T allele of IL28B rs12979860 polymorphism was documented against HCMV infection in the allogeneic stem cell transplant adult patients [8].

Finally, we found that TLR4 rs4986791 polymorphism was related to hepatitis in newborn infants with cCMV infection, but the pathomechanism of this finding is unclear. In previous reports, TLR4 rs4986791 polymorphism provoked the disruption of the normal structure of the extracellular domain of TLR4, what might generate a protein with reduced binding affinity to the ligand, what was reported as a protective factor against Helicobacter pylori infection among children with gastritis [40, 41]. Additionally, Bochud et al. showed that TLR4 rs4986791 (C/T T399I) had a protective effect against leprosy [42]. Nevertheless, ours is the first report that links SNPs of TLR4 and hepatitis in cCMV infection. Additional studies are needed to confirm the relation of TLR4 polymorphism with increased risk of hepatitis among cCMV-infected infants.

The strength of our study is the prospective character of the research. Another advantage is the homogenous study population, containing only the Caucasian newborn infants. Furthermore, we limited our study group to newborns with confirmed cCMV infection only, in order to eliminate other potential genetic factors of postnatal HCMV infection. To the best of our knowledge, five out of eight SNPs genotyped in the current study have never been analyzed in the context of cCMV infection.

The present study has also some limitations. We are aware that hypothesis-driven candidate gene approach is essentially gene association study, however, it is also a subject to the artefacts of spurious association findings. Genes examined in the current study had been previously implied and some of them had been replicated poorly. However, most of these genes were not performed in newborn infants or if they were performed in that age group, the study populations were comparable or even smaller than ours.

What is more, it seems that different genes may take part in predisposition to the disease, while others host genes might influence on the clinical manifestation of the disease. We admit that the situation might be more complicated than it was previously assumed. Moreover, there are plenty of other external factors that could impact on the results: different HCMV strains, primary or secondary maternal infection, time of the fetus infection (which trimester). However, the current study was not designed to address these issues.

We acknowledge that the power of association study is improved if the sampling strategy takes account of exposure heterogenity, though this is not necessarily easy to do, especially in the setting of cCMV infection. In addition, no correction for multiple testing was applied, and so type I error cannot be completely ruled out.

Nevertheless, our study group of 92 cCMV-infected newborns is larger than in our previous research, we are aware that the study sample size might be still not large enough as for genetic studies. Undoubtedly, future studies on cCMV infection are demanded to replicate above-mentioned findings in a much larger cohort. Moreover, there is a need for other studies of genetic characteristics of the unique and immature fetus-host and its predisposition to the infection, not only limiting to HCMV itself. We underline the necessity for meta-analytic studies in this subject.

To summarize, our study demonstrated new associations between SNPs in IL1B, IL12B, IL28B, TLR4 genes and symptoms of cCMV infection such as prematurity, splenomegaly, thrombocytopenia and hepatitis respectively. Further studies on the role of SNPs in the pathogenesis of cCMV infection and incorporation assessment of selected SNPs in the clinical practice are warranted.

Association between examined SNPs and abnormal MRI.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); MRI, magnetic resonance imaging; IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor. a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants with normal MRI and abnormal MRI in cCMV group.

(DOCX)

Click here for additional data file.

Association between examined SNPs and abnormal hearing.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor. a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants with normal hearing and abnormal hearing in cCMV group. c Abnormal hearing–was defined as air conduction thresholds > 20dBHL on the Auditory Brainstem Response (ABR) at least in one ear.

(DOCX)

Click here for additional data file.

Association between examined SNPs and cholestasis.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor. a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants without cholestasis and with cholestasis in cCMV group.

(DOCX)

Click here for additional data file.

Association between examined SNPs and IUGR.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IUGR, intrauterine growth restriction; IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor.a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants without IUGR and with IUGR in cCMV group.

(DOCX)

Click here for additional data file.

Association between examined SNPs and microcephaly.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor. a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants without microcephaly and with microcephaly in cCMV group.

(DOCX)

Click here for additional data file.

Association between examined SNPs and neutropenia.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor. a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants without neutropenia and with neutropenia in cCMV group.

(DOCX)

Click here for additional data file.

Association between examined SNPs and chorioretinitis.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor. a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants without chorioretinitis and with chorioretinitis in cCMV group. c With chorioretinitis–if occurred at least in one eye.

(DOCX)

Click here for additional data file.

Association between examined SNPs and petechiae.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor. a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants without petechiae and with petechiae in cCMV group.

(DOCX)

Click here for additional data file.

Association between examined SNPs and hepatomegaly.

Data presented as number (%), OR, odds ratio; CI, confidence interval; NA, not applicable; NS, not significant (p-values above 0.05); IL, Interleukin; CCL 2, C-C motif chemokine ligand 2; DC-SIGN, dendritic cell-specific ICAM-grabbing non-integrin; TLR, Toll-like receptor. a SNP database (dbSNP) reference number (ID number). b P-value for comparison between infants without hepatomegaly and with hepatomegaly in cCMV group.

(DOCX)

Click here for additional data file.

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

2 Mar 2020

PONE-D-20-04592

Association between single nucleotide polymorphisms (SNPs) of IL1, IL12, IL28 and TLR4 and symptoms of congenital cytomegalovirus infection.

PLOS ONE

Dear Prof. Czech-Kowalska,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised by two experts who reviewed your study.

Please address all points raised by the reviewers including the major concerns of Reviewer 1 who believes that the study approach is outdated and the manuscript should not be published. We will only be able to publish your work if these concerns are dispelled.

We would appreciate receiving your revised manuscript by Apr 16 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Michael Nevels

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at http://www.plosone.org/attachments/PLOSOne_formatting_sample_main_body.pdf and http://www.plosone.org/attachments/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. We noticed that you have chosen the subsection category “[FOR JOURNAL STAFF USE ONLY]” for your manuscript. Unfortunately, this is not a valid category. At this time, please choose one or more subsections that best represent the topic(s) of your study.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: No

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The manuscript topic is an outdated approach, where the variants in the known immune genes are associated with the CMV infection. These genes were previously implied in numerous studies, and replicated poorly, suggesting lack of real significance or at the least more complicated situation that previously assumed. Also, the focus of the clinically manifest disease will likely depend on the host genes, causing more selection bias in the study design. Lack of significance and traces of related phenotypes support this, and suggest an accidental finding (due to lack of multiple-testing adjustment, which is mandatory due to various genetic models being used in the analysis). The main hypothesis of this study should not be so focused on CMV itself (since the vast majority of people are positive), but to the underlying genetic characteristics that predispose some of these infected people/neonates towards infection. This is likely to be achieved through meta-analytic study. The current study is substantially underpowered, and hence of very limited contribution.

Reviewer #2: Authors should address the following points:

1. Table 1: summation of cCMV group (n=49) and control group (n=70) should be 119 not 129 for Cesarean section

2. In all tables the foot notes should clearly state to which groups’ statistical comparisons the P values belong to. (i.e. cCMV and control groups)

3. For tables where SNP genotypes are presented, for each SNP the change should be given. For example rs16944 (G/A)

4. Either in the Materials or in Introduction section why these candidate genes was chosen should be briefly explained (i.e. cytokines X,Y,Z were chosen for their pro-inflammatory role, etc.. ). This will also make the manuscript look more hypothesis driven.

5. AIC values presented in table 5 doesn’t convey much information as the reader doesn’t know the AIC values for other alternate models / effects of other not presented SNPs on a specific symptom.

6. Data on HCMV viral load, and maternal genotypes would also be interesting to examine

7. Thorough language, word usage, spelling check is advised.

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

15 Apr 2020

We are pleased to resubmit the revised version of our manuscript PONE-D-20-04592 entitled „Association between single nucleotide polymorphisms (SNPs) of IL1, IL12, IL28 and TLR4 and symptoms of congenital cytomegalovirus infection”.

We would like to thank the reviewers for their constructive comments. We have introduced changes according to the reviewers’ comments. All changes are highlighted in yellow in marked-up version of the article.

Please find our response to the reviewers’ comments, below:

Reviewer #1: The manuscript topic is an outdated approach, where the variants in the known immune genes are associated with the CMV infection. These genes were previously implied in numerous studies, and replicated poorly, suggesting lack of real significance or at the least more complicated situation that previously assumed. Also, the focus of the clinically manifest disease will likely depend on the host genes, causing more selection bias in the study design. Lack of significance and traces of related phenotypes support this, and suggest an accidental finding (due to lack of multiple-testing adjustment, which is mandatory due to various genetic models being used in the analysis). The main hypothesis of this study should not be so focused on CMV itself (since the vast majority of people are positive), but to the underlying genetic characteristics that predispose some of these infected people/neonates towards infection. This is likely to be achieved through meta-analytic study. The current study is substantially underpowered, and hence of very limited contribution.

Reply: We thank the reviewer for this important comment. Our study was single-centre and prospective one, conducted between 2016 and 2019 in homogenous population of Caucasian newborns. The methodology has been chosen based on current trends in the field of SNP associations with infectious diseases. Both hypothesis-driven candidate gene approach and genome-wide associations are essentially gene association studies as well as both are subject to the same artefacts of spurious association findings. In our study the former approach was chosen based on our previous expertise in the field and available resources. We used customized TaqMan Assay (rather than RLFP-PCR) which provide accurate and reproductive results. We acknowledged that the power of association study is improved if the sampling strategy takes account of exposure heterogeneity, though this is not necessarily easy to do, especially in the setting of congenital CMV infection. We also acknowledge the lack of correction for multi testing and these limitations were mentioned in the manuscript.

We appreciate the reviewer’s point of view that the main hypothesis of this study should not be so focused on CMV itself (since the vast majority of people are positive). We agree that the vast majority of people are positive. The prevalence of CMV seropositive women in reproductive age is about 80% in Poland (Siennicka_ High Seroprevalence of CMV Among Women of Childbearing Age Implicates High Burden of Congenital Cytomegalovirus Infection in Poland_ Polisch J Microbiol 2016). The prevalence of seropositive newborns would be similar - most of newborn infants are seropositive due to transplacental transfer of maternal IgG but not to congenital infection. Nevertheless, a rate of cCMV is only about 0,5 % (in Poland estimated rate is 2,2 to 3,7%). Additionally, immaturity of fetal immune system makes this population very unique and may influence on the role of immune genes variations in congenital infection. Therefore we decided to examine the association between SNPs in genes encoding selected cytokines and cytokine receptors in newborns (also preterms) with proven congenital CMV infection. We agree that these genes were previously implied in numerous studies, and replicated poorly, however most of them were not performed in newborn infants, and if they were performed, the study populations were comparable or even smaller than ours. We underlined the need for further studies in larger population in our manuscript. We also agree that meta-analysis incorporating published SNP genotyping data is warranted to evaluate factors which predispose neonates towards CMV infection, thus data collected in studies like ours is desirable.

Reviewer #2:

1. Table 1: summation of cCMV group (n=49) and control group (n=70) should be 119 not 129 for Cesarean section

Reply: We would like to thank the reviewer for attention to details. We have addressed this comment by correcting data in Table 1.

2. In all tables the foot notes should clearly state to which groups’ statistical comparisons the P values belong to. (i.e. cCMV and control groups)

Reply: We have followed reviewer’s recommendation and we are very grateful for this suggestion. We have added suitable information in the foot notes to state which groups’ statistical comparison were presented. We have presented that information by using “b” superscript in all footnotes.

3. For tables where SNP genotypes are presented, for each SNP the change should be given. For example rs16944 (G/A)

Reply: We would like to thank the reviewer for attention to details. We have supplemented the tables with information about the change in nucleotides for each SNP gene.

4. Either in the Materials or in Introduction section why these candidate genes was chosen should be briefly explained (i.e. cytokines X,Y,Z were chosen for their pro-inflammatory role, etc.. ). This will also make the manuscript look more hypothesis driven.

Reply: In the Material and Methods section, we have added additional section called “Candidate genes selection”, where we provided rationale for selecting individual SNPs for the study. We have supported it with additional appropriate references.

5. AIC values presented in table 5 doesn’t convey much information as the reader doesn’t know the AIC values for other alternate models / effects of other not presented SNPs on a specific symptom.

Reply: We appreciate the reviewer’s precise analysis of the presented data. We understand that our presentation of data within Table 5 was not adequately detailed. Following the reviewer’s comments, we have made all the data underlying our findings fully available for the reader. Thus, we have moved four tables concerning symptoms with statistical significant findings from the Supplementary File to the main article. We have created four separate tables (Table 5-8) for each symptom instead of combined Table 5 from the original version of the article.

In all new Tables, AIC values have been added, in order to allow readers to see the results of other alternate models. The best fitted model based on AIC for each SNP have been presented by using “ c” superscript in footnotes in all four new Tables (5 to 8).

As the supporting information, we left nine tables (Tables S1-9) concerning data associations between examined SNPs and other analyzed symptoms among cCMV group, where no statistical finding were observed.

We hope, that new presentation of our results is now more informative for the reader.

6. Data on HCMV viral load, and maternal genotypes would also be interesting to examine.

As far as HCMV viral load is concerned, we have put these data into separate article which is now being reviewed in other medical journal.

We agree that maternal genotypes would be interesting to explore but our current project was not designed to address those issues. This was dictated by the fact that the present study was a single-center and conducted in hospital with no maternity unit. However, we strongly agree that it would be worth to incorporate maternal genotypes into a new multicenter project in the future.

7. Thorough language, word usage, spelling check is advised.

We have proofread the paper to eliminate all languages spelling errors.

Submitted filename: Response to Reviewers1.docx

Click here for additional data file.

21 Apr 2020

PONE-D-20-04592R1

Association between single nucleotide polymorphisms (SNPs) of IL1, IL12, IL28 and TLR4 and symptoms of congenital cytomegalovirus infection.

PLOS ONE

Dear Prof. Czech-Kowalska,

Thank you for submitting your revised manuscript to PLOS ONE. We appreciate that the manuscript has been improved substantially. Please address the remaining minor points made by Reviewer 1 before we proceed to publication.

We would appreciate receiving your revised manuscript by Jun 05 2020 11:59PM. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. This file should be uploaded as separate file and labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. This file should be uploaded as separate file and labeled 'Manuscript'.

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Michael Nevels

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you; you have not provided responses to all of my statements; please, at the very least address some of these issues in the limitations section

Reviewer #2: Authors addressed the comments and corrections from both reviewers. Minor typos and grammatical issues can be handled by the journal.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: Yes: Efe Sezgin

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files to be viewed.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org. Please note that Supporting Information files do not need this step.

27 Apr 2020

We are pleased to resubmit the revised version of our manuscript PONE-D-20-04592R1 entitled „Association between single nucleotide polymorphisms (SNPs) of IL1, IL12, IL28 and TLR4 and symptoms of congenital cytomegalovirus infection”.

We would like to thank the reviewers for their constructive comments. We have tried to introduced changes according to the reviewers’ comments. Please find our response to the reviewers’ comments, below:

Reviewer #1: Thank you; you have not provided responses to all of my statements; please, at the very least address some of these issues in the limitations section

Reply: We thank the Reviewer for this comment to expand the limitation section in our article. Now, we hope that constructive remarks in this section make the article much more valuable for the readers and researchers. The improved limitation section is as below:

“The present study has also some limitations. We are aware that hypothesis-driven candidate gene approach is essentially gene association study, however, it is also a subject to the artefacts of spurious association findings. Genes examined in the current study had been previously implied and some of them had been replicated poorly. However, most of these genes were not performed in newborn infants or if they were performed in that age group, the study populations were comparable or even smaller than ours.

What is more, it seems that different genes may take part in predisposition to the disease, while others host genes might influence on the clinical manifestation of the disease. We admit that the situation might be more complicated than it was previously assumed. Moreover, there are plenty of other external factors that could impact on the results: different HCMV strains, primary or secondary maternal infection, time of the fetus infection (which trimester). However, the current study was not designed to address these issues.

We acknowledge that the power of association study is improved if the sampling strategy takes account of exposure heterogenity, though this is not necessarily easy to do, especially in the setting of cCMV infection. In addition, no correction for multiple testing was applied, and so type I error cannot be completely ruled out.

Nevertheless, our study group of 92 cCMV-infected newborns is larger than in our previous research, we are aware that the study sample size might be still not large enough as for genetic studies. Undoubtedly, future studies on cCMV are demanded to replicate above-mentioned findings in a much larger cohort. Moreover, there is a need for other studies of genetic characteristics of the unique and immature fetus-host and its predisposition to the infection, not only limiting to HCMV itself. We underline the necessity for meta-analytic studies in this subject. “

Submitted filename: Response to Reviewers_2.docx

Click here for additional data file.

29 Apr 2020

Association between single nucleotide polymorphisms (SNPs) of IL1, IL12, IL28 and TLR4 and symptoms of congenital cytomegalovirus infection.

PONE-D-20-04592R2

Dear Dr. Czech-Kowalska,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

With kind regards,

Michael Nevels

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

7 May 2020

PONE-D-20-04592R2

Association between single nucleotide polymorphisms (SNPs) of IL1, IL12, IL28 and TLR4 and symptoms of congenital cytomegalovirus infection.

Dear Dr. Czech-Kowalska:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Michael Nevels

Academic Editor

PLOS ONE