Cadmium and Chromium exposure associated with DNA hypermethylation of p16 tumor suppressor gene: a case–control study from endemic region of northern India

Abstract

This study investigates the environmental impact of urbanization on water quality in Greater Noida, a rapidly developing region in India. Thirty groundwater samples were collected from five villages during the pre-monsoon season using sterilized polypropylene bottles, and samples were acidified and digested with concentrated nitric acid prior to analysis. Chromium (Cr) and cadmium (Cd) concentrations in water were determined using Atomic Absorption Spectrophotometry (AAS), with mean pre-monsoon concentrations of 0.436 ± 0.237 ppb for Cr and 0.224 ± 0.091 ppb for Cd. A case–control study involving 25 cancer patients and 25 healthy individuals was conducted to explore the potential health effects of heavy metal exposure through drinking water. Blood samples were analyzed for Cd and Cr levels, and p16 gene promoter hypermethylation was assessed in whole blood leukocytes using methylation-specific PCR (MSP). The frequency of p16 hypermethylation was significantly higher in the exposed group (64%) compared to controls (8%) (p = 0.002). These findings demonstrate a strong association between heavy metal exposure and p16 hypermethylation, emphasizing the need for comprehensive monitoring, control measures, and remediation strategies to address environmental contamination and safeguard public health in swiftly urbanizing regions like Greater Noida.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-025-01957-2.

Introduction

Heavy metals such as cadmium (Cd) and chromium (Cr) are significant environmental pollutants with profound implications for human health due to their ability to induce oxidative stress, disrupt cellular signaling, and cause epigenetic modifications, including DNA hypermethylation [1]. Cadmium, a non-essential and highly toxic metal, is absorbed via inhalation, ingestion, or dermal contact, accumulating primarily in the kidneys and liver, where it disrupts antioxidant defenses and cellular homeostasis [2]. Mechanistically, cadmium exposure leads to oxidative stress by interfering with key antioxidant enzymes such as superoxide dismutase, catalase, and glutathione peroxidase, resulting in cellular damage and apoptosis [2, 3]. Furthermore, cadmium induces epigenetic modifications, notably DNA hypermethylation of tumor suppressor genes like p16, through the upregulation of DNA methyltransferases (DNMTs), contributing to carcinogenesis [4–6]. Cadmium also disrupts mitochondrial function, further exacerbating oxidative damage and cellular dysfunction [7].

Chromium, particularly in its hexavalent form [Cr(VI)], is classified as a Group I carcinogen and poses health risks through occupational and environmental exposure [8]. Upon cellular uptake, Cr(VI) undergoes metabolic reduction, generating reactive oxygen species (ROS) and causing DNA damage, including strand breaks and chromosomal abnormalities [8]. The inhalation of airborne Cr(VI) particles is associated with respiratory cancers, while oral exposure through contaminated water leads to systemic distribution and potential carcinogenic effects, notably in the lungs, liver, and kidneys[9].

Chromium exposure also induces DNA hypermethylation of tumor suppressor genes such as p16, impairs DNA repair mechanisms by downregulating genes like MGMT, and alters histone modifications and non-coding RNA expression, collectively promoting carcinogenesis and genomic instability [10, 11].

The health implications of cadmium and chromium exposure are substantial, with both metals linked to increased risks of various cancers (lung, breast, prostate, and kidney), renal dysfunction, and neurotoxicity as shown in Fig. 1 [8]. The hypermethylation of tumor suppressor genes, particularly p16, is a critical epigenetic event that facilitates cell cycle progression, apoptosis evasion, and malignant transformation [10, 11]. p16 (CDKN2A) is a crucial tumor suppressor gene that regulates the cell cycle by inhibiting cyclin-dependent kinases, thus preventing unchecked cell proliferation [12]. Its promoter hypermethylation leads to gene silencing, which has been frequently observed in various cancers and is associated with adverse clinical outcomes [13]. Importantly, heavy metals such as cadmium and chromium have been shown to induce epigenetic alterations, including p16 hypermethylation, which can serve as early biomarkers of carcinogenic risk [11, 14]. Investigating p16 methylation in populations exposed to these metals may provide valuable insights into early epigenetic changes that predispose individuals to cancer, highlighting its potential as a predictive biomarker for metal-related carcinogenesis [15]. Future investigations should explore additional tumor suppressor genes (such as RASSF1A, MGMT, and CDH1) and epigenetic markers to provide a broader and more comprehensive assessment of the epigenetic landscape related to heavy metal exposure.

Fig. 1.

Diagram depicting health issues associated with heavy metals

Environmental sources of cadmium include industrial emissions, agricultural contamination from phosphate fertilizers, and cigarette smoke [3]. Chromium is released through stainless steel production, electroplating, industrial waste, and occupational exposure [8].

Comparative analysis with other heavy metals such as arsenic, lead, mercury, and nickel reveals shared toxicity mechanisms, including oxidative stress induction, epigenetic modifications, and impaired DNA repair [10, 11]. However, differences exist; for example, lead disrupts heme synthesis through selective enzyme binding, while cadmium and chromium are more directly implicated in carcinogenesis through epigenetic gene silencing as shown in Table 1 [16].

Table 1.

Heavy metals and their health implications

Heavy metal	Primary exposure sources	Key toxicity mechanisms	Health implications	References
Cadmium	Mining, smelting, fertilizers, cigarette smoke	Oxidative stress, DNA hypermethylation, mitochondrial dysfunction	Renal dysfunction, cancers, neurotoxicity	[17]
Chromium	Industrial emissions, electroplating, waste	ROS generation, DNA hypermethylation, impaired DNA repair	Lung cancer, hepatic damage, neurodegenerative diseases	[3]
Arsenic	Contaminated water, pesticides, mining	Oxidative stress, epigenetic modifications, genomic instability	Skin and lung cancers, cardiovascular diseases	[2]
Lead	Paints, batteries, contaminated soil, and water	ROS generation, enzyme inhibition, neurotoxicity	Neurological deficits, renal damage, cardiovascular diseases	[8]

Understanding the molecular mechanisms of cadmium and chromium toxicity, particularly their roles in DNA hypermethylation and gene silencing, is essential for advancing risk assessment and developing targeted interventions to mitigate their adverse health effects [8, 10, 16].

These two metals were prioritized because of their high toxicity, abundance in the sampling sites, and documented linkage to epigenetic modifications like DNA hypermethylation of tumor suppressor genes (e.g., p16), which are crucial in cancer development, Moreover, the previous literature indicates that cadmium and chromium pose immediate health risks through mechanisms such as oxidative stress and gene silencing, making them relevant candidates for detailed analysis in correlation with DNA methylation status [17]. Consequently, the study focused on measuring and analyzing these metals to elucidate their specific impact on epigenetic alterations and potential carcinogenic pathways, with the understanding that other metals, if present at lower levels, might have less immediate relevance or were below detection thresholds.

Urbanization and industrialization are significant factors influencing environmental quality, particularly in rapidly developing regions like Greater Noida. While industrial discharges are well-known sources of heavy metals such as cadmium and chromium, urban expansion itself contributes to pollution through increased vehicular emissions, construction activities, and improper waste management. These processes often lead to the leaching and mobilization of toxic metals into groundwater and surface water bodies, posing substantial public health risks. Understanding the relative contributions of urbanization-driven activities and industrial sources is crucial for designing effective mitigation strategies. We hypothesize that elevated levels of chromium and cadmium in water sources are associated with increased DNA hypermethylation of the tumor suppressor gene p16 in exposed populations, thereby contributing to carcinogenesis. In this context, the present study aims to elucidate the extent of heavy metal contamination in water and its potential epigenetic effects on human health, focusing specifically on the impact of urban environmental changes associated with urban infrastructure growth, rather than solely industrial pollution sources.

The collection of pre- and post-monsoon samples was strategically designed to capture seasonal variations in heavy metal concentrations, which are known to fluctuate with environmental factors such as rainfall and runoff. These variations are particularly relevant when assessing potential health impacts, including cancer risk, as heightened metal levels during specific periods may contribute to genotoxic and epigenetic alterations. In this study, the focus on post-monsoon contamination levels is especially pertinent, given the significant increase in chromium and cadmium concentrations observed during this period. By analyzing the association between elevated post-monsoon heavy metal levels and biomarkers such as p16 hypermethylation, the research aims to evaluate whether these seasonal environmental changes are linked to an increased risk of carcinogenic molecular alterations. Clarifying that the primary investigation centers on post-monsoon metal levels enhances understanding of how seasonal exposure windows may influence cancer-related epigenetic modifications.

The present study involved the collection of water and blood samples to assess heavy metal contamination, specifically focusing, cadmium (Cd), and chromium (Ni). Water samples were collected from diverse sources, while blood samples were obtained from relevant populations to evaluate heavy metal exposure. In areas of India, heavy metal contamination is a pressing issue due to industrial discharges, agricultural activities, and improper waste management, which contribute to the accumulation of toxic metals in water sources. The study particularly explored the association between elevated cadmium and chromium levels and altered DNA methylation of the p16 gene, aiming to unravel the mechanistic links between such exposures and increased cancer risk. By adhering to regulatory standards set by the Bureau of Indian Standards (BIS) and the United States Environmental Protection Agency (USEPA), this research is vital for addressing the public health risks posed by heavy metal exposure and reinforcing the importance of maintaining water quality within permissible limits.

Material and methods

Study area

The geographical characteristics of Greater Noida, located at a latitude of 28.47°N and longitude of 77.50°E, are particularly relevant to this research due to their proximity to rapidly expanding industrial, commercial, and urban development zones. These features facilitate the accumulation and mobilization of pollutants, including heavy metals such as chromium and cadmium, through environmental pathways such as surface runoff and groundwater recharge. The area’s topography and hydrogeology may influence the dispersion and concentration of these contaminants, especially in regions experiencing significant urbanization and industrial activity. Understanding how geographic and anthropogenic factors intersect is crucial for identifying potential sources of pollution, assessing exposure risks, and designing targeted remediation strategies to mitigate health impacts on local populations.

Water sampling

In pursuit of research objectives, we systematically collected thirty groundwater samples in triplicates from five distinct villages using sterilized 1-L polypropylene bottles. Each sample was labeled as A1–A6, B1–B6, S1–S6, K1–K6, and D1–D6 and was collected from sampling location as shown in Fig. 2. These samples were drawn from various hand-pumps and bore wells within the villages. To capture seasonal variations, we collected triplicate samples during both the pre-monsoon (April–May) and post-monsoon (November–December) periods.

Fig. 2.

Map of study area

Collecting samples during different seasons is essential for capturing the temporal variability in pollutant levels driven by environmental factors such as rainfall and surface runoff. Seasonal variation, particularly during the monsoon, can significantly influence the mobilization, transport, and concentration of heavy metals such as chromium and cadmium in water sources. These fluctuations not only affect the environmental chemistry but also have direct implications for human exposure and ecosystem health, as elevated pollutant levels during the post-monsoon period may increase the risk of health issues, including carcinogenic epigenetic modifications such as p16 hypermethylation. Monitoring these seasonal changes allows for a comprehensive assessment of periods of heightened exposure risk, informing targeted public health interventions and sustainable water management strategies. Polypropylene bottles were used which were rinsed with sample water to prevent contamination before actual sample collection. Samples were collected, labeled, and stored carefully at 4 °C. Within 48 h of sampling, we conducted heavy metal (Cr and Cd) analysis of the water samples. Additionally, we recorded the coordinates of each sampling location using a handheld GPS device from the GARMIN GPSMAP 78S series.

This case–control study involved 25 recently diagnosed cancer patients (cases) and 25 healthy individuals (controls). The cases were residents of the Greater Noida Villages, relying on well and tap water as their primary drinking water source. The study, conducted from January 2023 to December 2023, and included patients with various cancers (breast cancer, oral cancer, prostate cancer, non-small cell lung cancer, esophageal cancer, and gallbladder carcinoma). Data on occupational history, smoking habits, tobacco chewing, drinking water history and conditions, past medical history, and reproductive history were collected through face-to-face interviews using a specially designed questionnaire. Inclusion criteria for cases included recent cancer diagnosis and groundwater reliance, while exclusion criteria ruled out prior cancer history and recent supplement use. Controls were similarly from the same region, free from illness, ensuring that differences in p16 methylation could be more accurately linked to heavy metal exposure. Patients with a positive family history of cancer and those using trace element and metal supplements in the past 3 months were excluded. Ethical approval was obtained from Sharda University, Greater Noida. Informed consent was secured from each patient before enrollment. Venous blood samples (2 mL) were collected from both cancer patients and the control group. The determination of serum concentrations of Cd and Cr was performed using an Atomic Absorption Spectrophotometer.

Analysis of heavy metals in both blood and water samples

To assess metal concentrations, we employed a Shimadzu Electro-thermal Graphite Furnace Atomic Absorption Spectrophotometer (GF-AAS) equipped with a Self-Reversal method background correction (BGC-SR) and High-speed Deuterium (BGC-D2) auto-sampler (Shimadzu Corporation, Japan). Standard metal solutions were prepared at five different concentrations, and absorbance (A) values were determined. Calibration curves were established within the concentration range, exhibiting linearity with regression coefficients (R2) exceeding 99.9%. Each water sample was aspirated into the AAS, and the absorbance was used to quantify the metal content via the calibration curve. This process was repeated thrice, and average concentrations were calculated.

For the collection of water samples, sterilized polypropylene bottles were used to minimize the risk of contamination and adsorption of heavy metals onto the container walls, as recommended in standard protocols (APHA, 2017; Sharma et al., 2022). Prior to sampling, each bottle was thoroughly rinsed with the water to be sampled. Immediately after collection, concentrated nitric acid (HNO₃) was added to each sample to lower the pH below 2. This acidification serves two primary purposes: It prevents the precipitation and adsorption of metals onto the container walls, and it stabilizes the metals in solution by inhibiting oxidation or microbial activity [18, 19]. All samples were then transported to the laboratory under cooled conditions and subsequently digested with concentrated nitric acid prior to analysis by Atomic Absorption Spectrophotometry. This procedure is consistent with established methods for trace metal analysis in water [18, 20].

For blood samples, 1.0 mL of whole blood was placed in separate beakers. Subsequently, 10.0 mL of freshly prepared concentrated nitric acid (65%) was added and allowed to stand for 10 min. The beakers were covered and subjected to digestion at 60–70 °C for 90 min. Next, 2 mL of nitric acid was introduced, and heating continued on a hot plate at approximately 80 °C until a clear digested solution was obtained. Excess acid was evaporated, and the resulting semi-dry mass was cooled and diluted with 0.1 mL nitric acid. These solutions were transferred to 50.0 mL volumetric flasks and diluted to the mark with distilled water (Ahmed et al., 2020). The concentrations of cadmium (Cd) and chromium (Cr) were determined using an Atomic Absorption Spectrophotometer (AAS). Standard metal solutions were prepared following AAS procedures to establish the calibration curve.

To screen p16 gene for promoter hypermethylation in various cancers

An approved paired case–control study was carried out after taking the ethical clearance from Institutional ethical committee, Sharda Hospital, Sharda University, Greater Noida. Twenty-five case subjects were enlisted from Greater Noida residing in villages with elevated chromium and cadmium levels in drinking water. Selection criteria included a documented drinking water history. Twenty-five control samples were matched for age, sex, ethnicity, and socioeconomic status from the same cadmium and chromium exposed villages. The descriptive characteristics of study participants, with no statistically significant differences observed between case and control groups.

The study used a case–control design with methylation-specific PCR (MS-PCR) to assess p16 promoter methylation in blood leukocytes. DNA was extracted, bisulfite-modified, and amplified with primers for methylated and unmethylated sequences; PCR products were analyzed by gel electrophoresis, with a ~ 150 bp band indicating methylation [21, 22]. Statistical analysis involved Chi-square tests and odds ratios to compare methylation frequencies, considering covariates such as smoking and water exposure. MS-PCR was selected for its practicality and efficiency in detecting methylation status across multiple samples, while the authors recognize that incorporating quantitative approaches such as bisulfite sequencing in the future studies could further enhance the precision and depth of methylation analysis.

The specific primer sequences were as follows:

Unmethylated Primers:

• Forward: 5′-TTATTAGAGGGTGGGGTGGATTGT-3′

• Reverse: 5′-CAACCCCAAACCACAACCATAA-3′

Methylated Primers:

• Forward: 5′-TTATTAGAGGGTGGGGCGGATCGC-3′

• Reverse: 5′-GACCCCGAACCGCGACCGTAA-3′

Polyacrylamide gel electrophoresis was used to analyze the PCR products. The presence of a ~ 150 bp band indicated p16 methylation in the blood.

Results

There is a noticeable increase in chromium concentrations in several samples during the post-monsoon period compared to the pre-monsoon period as shown in Table 2. In terms of the EPA’s MCL for total chromium in drinking water, set at 100 parts per billion (ppb), the results reveal that several samples during the post-monsoon period exceeded this regulatory limit. For instance, Sample A2 exhibited a significant increase from 0.835 to 2174 ppb, and Sample A5 demonstrated an increase from 0.459 to 2391 ppb. In accordance with the Indian Standard IS 10500, which establishes the regulatory value for total chromium in drinking water at 50 parts per billion (ppb) or 50 µg per liter (µg/L), the data indicate a breach of the regulatory limit. Both Sample A2 (2174 ppb) and Sample A5 (2391 ppb) showed chromium concentrations well above the permissible limit. Notably, during the pre-monsoon period, Sample K1 displayed a relatively high concentration of 0.735 ppb, while Sample A3 exhibited a lower concentration of 0.337 ppb. Comparing these values with the U.S. Environmental Protection Agency’s (EPA) Maximum Contaminant Level (MCL) for total chromium in drinking water, set at 100 parts per billion (ppb), both Sample K1 (0.735 ppb) and Sample A3 (0.337 ppb) are well below this regulatory limit.

Table 2.

Chromium and cadmium concentration both pre- and post-monsoon

S. No.	Latitude, Longitude	Chromium concentration (pre-monsoon) (ppb)	Chromium concentration (post-monsoon) (ppb)	Standard deviation	Cadmium concentration (pre-monsoon) (ppb)	Cadmium concentration (post-monsoon) (ppb)	Standard deviation
A 1	28.60606, 77.49602	0.753	652	460.50	0.097	49	34.57
A2	28.60369, 77.49528	0.835	2174	1536.65	0.156	48	33.83
A3	28.602069, 77.494213	0.337	ND	0.235	0.201	44	30.97
A4	28.59706, 77.50084	0.456	1487	1051.14	0.234	98	69.13
A5	28.59692, 77.50186	0.459	2391	1690.36	0.345	96	67.63
A6	28.59652, 77.50506	0.678	1675	1183.92	0.368	97	68.32
S1	28.58769, 77.51106	0.351	1845	1304.36	0.228	99	69.84
S2	28.58760, 77.58045	0.139	1945	1375.22	0.144	104	73.43
S3	28.58947, 77.51042	0.284	Not detected	0.20	0.223	96	67.72
S4	28.58741, 77.51225	0.284	Not detected	0.20	0.223	97	68.43
S5	28.58930, 77.51334	0.384	1995	1410.40	0.253	92	64.87
S6	28.59930, 77.51434	0.389	1990	1406.87	0.258	96	67.70
D1	28.61352, 77.51456	1.202	2321	1640.34	0.242	87	61.34
D2	28.61851, 77.49194	0.17	2391	1690.57	0.135	88	62.12
D3	28.614457, 77.51677	0.235	2397	1694.76	0.129	86	60.71
D4	28.61675, 77.51715	0.175	2275	1608.54	0.189	89	62.79
D5	28.62128, 77.51763	0.235	3145	2223.68	0.129	85	60.01
D6	28.63128, 77.51864	0.235	3145	2223.68	0.129	85	60.01
K1	28.60934, 77.48806	0.735	1522	1537.04	0.198	100	70.57
K2	28.61194, 77.48878	0.291	2174	1537.04	0.298	105	74.03
K3	28.61174, 77.48894	0.713	Not detected	0.50	0.386	121	85.28
K4	28.612596, 77.492087	0.341	652	460.79	0.498	109	76.72
K5	28.60308, 77.49164	0.291	2391	1690.48	0.298	96	67.67
K6	28.61319, 77.50164	0.291	2391	1690.48	0.298	96	67.67
B1	28.61396, 77.50195	0.377	2391	1690.42	0.213	98	69.14
B2	28.61131, 77.50140	0.69	2381	1683.13	0.221	97	68.43
B3	28.61467, 77.50110	0.491	1304	921.72	0.169	100	70.59
B4	28.61429, 77.49549	0.466	1957	1383.47	0.154	98	69.18
B5	28.60352, 77.49508	0.398	1959	1384.94	0.147	99	69.89
B6	28.60489, 77.49802	0.398	1959	1384.94	0.147	99	69.89

It has been observed that the post-monsoon samples (Sample A2 Sample A5, Sample D1…D6) surpassed the IS 10500 limit, indicating a notable increase in chromium concentration due to increased precipitation and mobilization of heavy metals in the environment. The monsoon season may enhance the leaching of chromium and cadmium from geological formations, soil, or other sources leading to elevated concentration in water (Lindfors et al., 2020). The regions sampled are known to be influenced by agricultural activities, urban runoff, and informal industrial operations, which may contribute to elevated chromium levels, especially during the post-monsoon period due to increased mobilization of pollutants. We acknowledge that identifying specific industrial or anthropogenic sources is essential for targeted interventions. Future studies should incorporate detailed environmental source apportionment analyses, including industrial activity mapping and analyses of potential pollution point sources, to better understand the origins of heavy metal contamination.

The observed increases in chromium levels during the post-monsoon period, coupled with the exceedance of both the EPA MCL and the IS 10500 regulatory value, highlight the critical importance of comprehensive actions to address potential environmental contamination. Chromium, often associated with industrial activities such as metal plating and tanning processes, can have adverse effects on ecosystems and human health when present in elevated concentrations. Thus, proactive monitoring, stringent control measures, and effective remediation strategies are crucial to prevent further contamination and safeguard the quality of drinking water sources. In contrast, the post-monsoon period exhibits a significantly higher standard deviation of 924.18. This indicates a substantial variation or dispersion in chromium concentrations among the samples during this period. The large standard deviation suggests that the chromium levels in the post- monsoon samples were widely spread, with some samples showing exceptionally high concentrations.

These standard deviation values shed light on the degree of variation in chromium concentrations and provide a measure of the data’s dispersion within each period. The higher standard deviation in the post-monsoon period suggests the possibility of additional sources or factors contributing to the observed variability in chromium levels during this time.

It was observed that both the mean and standard deviation of the post-monsoon cadmium levels are higher compared to the pre-monsoon levels as shown in Table 3. Additionally, the maximum value of the post-monsoon data significantly exceeds the limit of 3 ppb, indicating clear non-compliance, with values ranging from 44 to 100 ppb. To further analyze the data, we can compare the measured cadmium levels against the limit of 3 ppb. In Pre-Monsoon Data, all measured values are below the limit of 3 ppb, indicating compliance with the specified limit. In Post-Monsoon Data, all of measured values (30 out of 30) exceed the limit of 3 ppb, suggesting non-compliance with the specified limit.

Table 3.

Pre- and post-monsoon cadmium levels

Pre-monsoon cadmium levels	Post-monsoon cadmium levels
Mean: 0.2092 ppb	Mean: 86.04 ppb
Standard Deviation: 0.1232 ppb	Standard Deviation: 20.24 ppb
Minimum: 0.097 ppb	Minimum: 44 ppb
Maximum: 0.498 ppb	Maximum: 100 ppb

The study measured cadmium and chromium concentrations across 30 water samples. The mean concentration of chromium was 0.436 mg/L with a standard deviation of 0.237 mg/L, while cadmium’s mean concentration was 0.224 mg/L with a standard deviation of 0.091 mg/L. The minimum and maximum values for chromium were 0.139 and 1.202 mg/L, respectively, while for cadmium, they ranged from 0.097 to 0.498 mg/L as shown in Table 4. Overall, the data suggest that although chromium was present at higher concentrations in these pre-monsoon samples, cadmium poses a greater health risk due to its much lower permissible limit (3 ppb for cadmium vs 50 ppb for chromium), making even low levels of cadmium more hazardous.

Table 4.

Comparing chromium and cadmium concentration during pre-monsoon season

Variable	No. of observations	Minimum value	Maximum value	Mean	Standard deviation
Chromium Conc. (ppb)	30	0.139	1.202	0.436	0.237
Cadmium Conc. (ppb)	30	0.097	0.498	0.224	0.091

The Shapiro–Wilk test was conducted to evaluate the normality of the chromium and cadmium concentration data as shown in Table 5. The results (p = 0.002 for chromium and p = 0.018 for cadmium) indicated that the data significantly deviate from a normal distribution, thus violating the assumptions required for parametric tests. Therefore, the Wilcoxon signed-rank test, a non-parametric alternative that does not presume normality, was appropriately employed to compare paired pre-monsoon and post-monsoon samples. A non-parametric Wilcoxon signed-rank test was employed to investigate potential differences in the distributions of pre-monsoon chromium concentration (V) and cadmium concentration (V*) (n = 327) as shown in Fig. 3. The test statistic (V = 327) and its standardized value (V* = 3.848) indicated a substantial deviation from the expected value (175.500) under the assumption of identical distributions as mentioned in Fig. 3. The calculated variance (V = 1549.875) further supported this observation. Notably, the exact p-value could not be computed, but an approximation resulted in a highly significant value (p < 0.000). This outcome suggests that the distributions of these two variables differ significantly.

Table 5.

Shapiro–Wilk test (chromium/cadmium) for pre-monsoon level

	Chromium	Cadmium
W	0.871	0.913
p-value (two-tailed)	0.002	0.018
Alpha	0.05	0.05

Fig. 3.

Results of the Wilcoxon signed-rank test comparing pre-monsoon and post-monsoon chromium and cadmium concentrations in water samples. The boxplots depict the distribution and median values; the asterisk indicates statistically significant differences (p < 0.05)

X-axis: The plot represents the concentrations of two heavy metals, chromium (Cr) and cadmium (Cd), during the pre-monsoon season. Each metal is plotted as a separate strip.

Y-axis: The concentration of each metal is measured in parts per billion (ppb).

This strip plot compares the pre-monsoon concentrations of chromium and cadmium in water samples as shown in Fig. 4. The individual green lines represent the actual data points for both metals, while the red horizontal lines show the mean concentrations. The plot suggests that chromium levels are generally higher and more variable compared to cadmium. The statistical test results (p < 0.0001) indicate that the difference in concentrations between chromium and cadmium is highly significant, meaning the concentration of chromium is significantly different from cadmium in the water samples collected before the monsoon.

Fig. 4.

Strip plots illustrating the distribution of chromium (Cr) and cadmium (Cd) concentrations in water samples during the pre-monsoon season. The green lines represent individual sample points; the red horizontal lines denote mean concentrations. A significant difference (p < 0.0001) between metal levels is indicated

A paired case–control study on human blood samples was conducted after taking ethical clearance from Sharda School of medical Science and Research & Sharda Hospital, Greater Noida. The presence of p16 methylation in the blood is shown by the formation of a band size of approx.150 bp. As shown in Table 6, 16 of 25 (64%) subjects in high chromium and cadmium exposure group had p16 hypermethylation. In sharp contrast, only 2 of 25 (8%) subjects in control group exhibited p16 methylation. These results suggest that there is a significant correlation between p16 hypermethylation and the presence of chromium and cadmium in water.

Table 6.

Frequency of p16 hypermethylation in study groups

S. No.	Group	p16 methylated	p16 unmethylated	Total no. of samples	Standard deviation	p value
1	Chromium and cadmium exposure	16 (64%)	9	25	0.65064	0.002
2	Control	2 (8%)	23	25	0.52599	0.265

The results indicate that there are significant differences between p16-methylated and p16-unmethylated samples in both the Cr and Cd exposure group as well as the control group as shown in Table 6. The differences are statistically significant based on the p-values provided. The values for the standard deviation and margin of error give an idea of the variability of the data within each group. Figure 5 represents frequency of p16 methylation in cancer patients among Greater Noida population.

Fig. 5.

MSB (Methylation-Specific Band) and UMSB (Unmethylation-Specific Band) of p16 in blood samples of cancer patients (Lane no.1-Ladder, Lane no. 2, 4-Methylation-Specific bands in blood samples of cancer patients, and Lane no. 3, 5-Unmethylation-specific bands in blood samples of cancer patients)

The p-value of 0.03 is less than the commonly used significance level of 0.05. The methylation of p16 gene showed a significant risk of developing cancer in patients (Table 7). p16 was observed to be methylated in 36 percent of smokers among patients. It was only 8 percent among controls suggests a 4.5-fold higher prevalence of p16 methylation in the patient group that aligns with prior research showing p16 promoter hypermethylation is a biomarker for cancer risk, including breast and lung cancers [23].

Table 7.

Frequency of methylation of p16 gene and smoking status in cancer patients and healthy controls

Gene	Methylation status	Cases [25]	Control [25]	OR	95% CI	p value
P16	M	9(36%)	2(8%)	1.0737	0.44–0.84	0.03

In Table 8, the data presented reveal significant findings concerning the p16 Hypermethylation-Water group, with a 95% confidence interval ranging from 0.70857 to 3.381 and a t-value of 24, leading to a statistically significant p-value of 0.002. This suggests a notable difference in this group, implying potential implications regarding p16 gene hypermethylation. Conversely, the Control-Water group, evidenced by a narrower confidence interval from − 1.141 to 0.09712 and a non-significant p-value of 0.265, indicates that any observed variations within this group are likely attributable to random chance rather than a meaningful difference from a reference.

Table 8.

Frequency of methylation of p16 gene and years of drinking groundwater of Greater Noida Villages

S. No	Group	95% confidence interval	t	df	p value
1	p16 hypermethylation-water	0.70857	3.381	24	0.002
2	Control-water	0.09712	1.141	24	0.265

Discussion

The results presented in the study reveal a significant increase in chromium concentrations during the post-monsoon period, with several samples exceeding regulatory limits established by both the U.S. Environmental Protection Agency (EPA) and the Indian Standard IS 10500. Notably, the post-monsoon samples (Sample A2 and Sample A5) surpassed the IS 10500 limit, indicating a notable increase in chromium concentration potentially attributed to increased precipitation and mobilization of heavy metals in the environment.

The observed variations in chromium levels during the post-monsoon period, as indicated by the significantly higher standard deviation, point to potential additional sources or factors contributing to the variability in chromium concentrations. The large standard deviation implies that chromium levels were widely spread, with some samples exhibiting exceptionally high concentrations during this time.

Furthermore, the statistical analysis of cadmium levels during the post-monsoon period indicates higher mean values, greater variability, and a larger number of measurements exceeding the specified limit of 3 ppb compared to the pre-monsoon levels. This suggests potential non-compliance with regulatory limits during the post-monsoon period, emphasizing the need for thorough monitoring and remediation efforts to address environmental contamination.

Exposure to non-essential metals, such as cadmium and chromium, is pervasive and has been associated with epigenetic alterations, particularly in DNA methylation [24]. Environmental exposure to chromium has been linked to differential DNA methylation, with significant findings indicating differentially methylated positions (DMPs) and differentially methylated regions (DMRs) associated with DNA damage and genomic instability [25]. Concurrently, cadmium exposure has been implicated in the development or progression of various health issues, including cancers, cardiovascular dysfunction, nephrotoxicity, and bone damage [26]. Importantly, the inactivation of the tumor suppressor gene p16INK4a is identified as a common mechanism through CpG island hypermethylation [21]. The widespread exposure to both essential and non-essential metals underscores the need for a comprehensive understanding of the epigenetic consequences and associated health risks.

In addition to the presented findings, it is crucial to contextualize these results within the broader body of scientific literature. Several prior studies have investigated the impact of heavy metal contamination, including chromium and cadmium, on water quality and human health. Similar trends were found in increased chromium concentrations during certain seasons, supporting the idea that environmental factors, such as precipitation, can influence metal mobilization [27]. Additionally, Coetzee et al. [28] demonstrated the adverse effects of elevated chromium and cadmium levels on ecosystems and human health, reinforcing the importance of proactive monitoring and stringent control measures.

Furthermore, the paired case–control study on human blood samples conducted in this study provides valuable insights into the correlation between p16 hypermethylation and the presence of chromium and cadmium in water. This finding aligns with existing research on the genotoxic effects of heavy metal exposure, as highlighting the potential health implications associated with metal contamination. The small sample size of 25 cases and 25 controls limits the statistical power of the methylation analysis, making these findings exploratory. Future studies with larger cohorts are needed to confirm these results and clarify the relationship between heavy metal exposure and p16 methylation in Greater Noida population.

One noteworthy aspect of our study is the use of whole blood leukocytes for p16 methylation analysis. While it is a non-tissue-specific approach, it has been successfully employed in previous investigations of disease-related epigenetic changes. However, we acknowledge that future studies incorporating samples from relevant tissue types, such as affected skin regions, could provide more precise insights into the epigenetic alterations induced by cadmium and chromium exposure.

Our results support and expand upon previous research that has demonstrated the epigenetic effects of environmental toxicants, including heavy metals [11]. Notably, the qualitative nature of the methylation-specific PCR (MS-PCR) assay we employed in this study warrants further validation and quantitative assessment through techniques like bisulfite sequencing [29]. Such approaches would enhance the precision of our findings and provide a more comprehensive understanding of the correlation between cadmium and chromium exposure levels and p16 methylation.

The relationship between heavy metal exposure and p16 hypermethylation has been established in the literature, our study specifically investigates this association within the context of the Greater Noida population. Such epigenetic modifications can vary significantly across different populations due to genetic, environmental, and lifestyle factors. Therefore, our findings contribute valuable, region-specific data that highlight potential environmental health risks in this area. We acknowledge that the sample size and study design may limit the generalizability of our results, and further large-scale, population-specific studies are necessary to confirm these associations.

However, it is imperative to investigate whether the observed epigenetic silencing of p16 translates into functional consequences, such as reduced RNA and protein expression. Future research efforts should aim to elucidate the direct impact of p16 hypermethylation on its expression and its role in the development of related diseases, including cancer.

The results of this study have important implications for public health, particularly in regions with elevated cadmium and chromium exposure levels. Although our study demonstrates a significant association between p16 methylation and cancer risk in populations exposed to cadmium and chromium, we did not evaluate the reversibility of this epigenetic change or the therapeutic potential of DNMT inhibitors. Given that p16 methylation is potentially reversible and DNMT inhibitors are clinically available, future research should investigate whether pharmacological reversal of tumor suppressor gene hypermethylation could mitigate cancer risk in individuals with heavy metal exposure [30, 31]. The results of this study underscore the critical importance of addressing elevated chromium and cadmium concentrations in water, emphasizing the need for comprehensive actions to prevent further environmental contamination and protect human health.

Chromium (VI) exposure in humans has been associated with increased mortality and a higher incidence of various cancers, including lung, throat, bladder, kidney, testicular, bone, and thyroid cancers [32, 33]. An ecological study conducted in Greece in 2011 revealed elevated levels of chromium (VI) in drinking water, which correlated with an increased prevalence of genitourinary malignancies in women, as well as lung and liver cancers [15]. Additionally, groundwater contaminated with chromium (VI) in India has been linked to higher rates of gastrointestinal and dermatological issues [15].

The mechanisms underlying chromium toxicity and carcinogenicity are well-established. Both chromium (VI) and chromium (III) can generate reactive oxygen species (ROS), leading to DNA damage and genomic instability [32]. Epigenetic effects of chromium exposure have been observed, including global DNA hypomethylation and promoter-specific DNA methylation. These alterations contribute to genomic instability and gene silencing in various cancers and human disorders [15].

Studies since 2002 have demonstrated that chromium (VI) exposure induces DNA methylation and gene silencing, resulting in subsequent epigenetic changes associated with cancer development [15]. Notably, CpG sites on the p16 gene exhibit significant methylation in human bronchial epithelial cells exposed to chromium (VI), negatively correlating with p16 mRNA expression. Furthermore, lung tumor samples from workers exposed to chromate display methylation of tumor suppressor genes such as APC, hMLH1, and MGMT [15].

Cadmium exposure, particularly to cadmium (II), has been associated with DNA hypermethylation, potentially leading to altered gene expression and disease onset, including cancer [14]. Cadmium exposure may enhance the activity of DNA methyltransferase (DNMT) enzymes, altering methylation patterns in specific genes [14]. The tumor suppressor gene p16, or CDKN2A, plays a crucial role in regulating cell cycle progression and inhibiting cellular transformation [12].

Importantly, DNA hypermethylation frequently silences p16 in human tumors in addition to genetic loss and mutation [13]. This study conducted a thorough analysis of heavy metal contamination in water resources, emphasizing its global impact on human health and the environment. The study encompassed regional investigations, regulatory frameworks, and recent research findings to contribute to a better understanding of the challenges posed by heavy metal contamination. Assessment of skin lesions such as melanosis, keratosis, or hyperkeratotic changes was not included in the present study and represents an important area for future investigation in individuals with long-term cadmium or chromium exposure.

Conclusion

In conclusion, the comprehensive analysis of chromium and cadmium concentrations in water samples during pre-monsoon and post-monsoon periods has provided valuable insights into potential environmental contamination. The notable increase in chromium levels during the post-monsoon period, exceeding both the U.S. EPA and Indian Standard IS 10500 regulatory limits, underscores the urgency of addressing heavy metal contamination. The elevated standard deviation in post-monsoon chromium levels suggests diverse sources contributing to the observed variability.

Similarly, the statistical analysis of cadmium levels revealed higher mean values, increased variability, and a significant number of measurements surpassing the specified limit during the post-monsoon period. This points toward potential non-compliance and emphasizes the need for rigorous monitoring and remediation efforts. The paired case–control study on human blood samples further highlights a significant correlation between p16 hypermethylation and the presence of chromium and cadmium in water, underscoring potential health implications associated with metal contamination.

The study contributes to the existing body of knowledge by providing context-specific insights into seasonal variations, environmental factors influencing metal mobilization, and the genotoxic effects of heavy metal exposure. It emphasizes the critical importance of proactive measures, stringent control, and effective remediation strategies to safeguard water quality, prevent further contamination, and protect both ecosystems and human health. As environmental challenges persist, continued research and collaborative efforts are required to ensure sustainable and safe water resources for future generations which would help in attaining the goals of sustainable development.

Author contributions

A.K.J conceptualize the research idea. R.M. wrote the main manuscript under the guidance of A.K.J. G.S., S.P.S., and A.K.J. provided further conceptual guidance. All authors reviewed and approved the final version of the manuscript.

Funding

No funding provided.

Availability of data and material

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Taken from Sharda School of Medical Sciences and Research &Hospital, Sharda University, Greater Noida, Uttar Pradesh, India.

Consent for publication

NA.

Competing interests

The authors declare no competing interests.