ABSTRACT

Objective

Poly (ADP-ribose) polymerase-1 (PARP-1) is a key enzyme in DNA repair pathways and has been implicated in cancer susceptibility. The rs1136410 polymorphism in the PARP-1 gene has shown inconsistent associations with gastrointestinal cancer risk across populations. This meta-analysis aimed to evaluate the association between PARP-1 rs1136410 polymorphism and the risk of colorectal cancer (CRC) and gastric cancer (GC), with a focus on ethnic differences.

Methods

A systematic literature search was performed in PubMed, Scopus, EMBASE, Web of Science, Cochrane Library, BIOSIS, LILACS, CNKI, CBM, Wan Fang, and other regional databases up to February 1, 2025. Eligible case-control studies assessing the association between PARP-1 rs1136410 polymorphism and CRC or GC were included. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated under five genetic models using Comprehensive Meta-Analysis software.

Results

Thirteen case-control studies were included, comprising 3.591 patients and 5.433 controls. For GC (8 studies; 1,784 cases and 2,521 controls), significant associations were observed under multiple genetic models: allele comparison (C vs. T: OR=2.01, 95% CI 1.04-3.91, p=0.039), homozygous comparison (CC vs. TT: OR=1.77, 95% CI 1.24-2.52, p=0.002), heterozygous comparison (CT vs. TT: OR=1.36, 95% CI 1.18-1.57, p<0.001), and recessive comparison (CC vs. CT+TT: OR=1.54, 95% CI 1.08-2.20, p=0.017). No significant association was detected for CRC (5 studies; 1.807 cases and 2.912 controls). Ethnic subgroup analysis revealed a protective effect against CRC in Caucasians but increased susceptibility in Asians.

Conclusion

The PARP-1 rs1136410 polymorphism is associated with elevated GC risk but not CRC, with ethnicity-dependent effects suggesting differential genetic susceptibility. These findings highlight the importance of considering population-specific genetic backgrounds in gastrointestinal cancer risk assessment, prevention, and precision medicine strategies.

INTRODUCTION

Gastrointestinal cancers, particularly colorectal cancer (CRC) and gastric cancer (GC), pose a significant global health challenge¹. In the US, 2024 projections estimate 152,810 new CRC diagnoses (81.540 in males, 71.270 in females) and 53.010 deaths (28.700 men, 24.310 women)^2-4. CRC incidence and mortality exhibit racial/ethnic disparities, with Black Americans experiencing the highest rates, followed by Native Americans. Hispanic and Asian American/Pacific Islander populations show lower incidence, with Hispanic populations having better outcomes than non-Hispanic Whites^5-7. These disparities stem from complex interactions of genetics, environment, and social determinants. GC has a distinct profile, with approximately 26,890 new cases (16.160 in males, 10.730 in females) and 10.880 deaths projected for 2024. Unlike CRC, GC incidence is higher among the Asian and Hispanic populations, as well as non-Hispanic Black Americans^8-10. GC etiology includes Helicobacter pylori infection, tobacco use, diet, and familial predisposition, highlighting gene-environment interactions^{11, 12}. Understanding these patterns is crucial for investigating genetic polymorphisms influencing cancer risk¹³.

Poly (ADP-ribose) polymerase-1 (PARP-1), also known as ADPRT, PARP, and NAD(+)-glycohydrolase, is crucial in the DNA damage response and repair via poly (ADP-ribosyl)ation^{14, 15}. In CRC, PARP-1 has a dual role, inhibiting tumor initiation via its interaction with the DNA repair protein O6-methylguanine-DNA methyltransferase, and promoting tumor progression influenced by genetic and environmental factors^{16, 17}. Increased PARP-1 mRNA and protein levels are associated with worse outcomes in CRC, particularly in tumors with mutated p53^18-20. PARP-1 might also contribute to the cancer stem cell phenotype, essential for tumor aggressiveness and recurrence^{18, 21}. In GC, high PARP-1 expression is associated with aggressive tumor traits such as invasion and metastasis, with specific single nucleotide polymorphisms of the PARP-1 gene linked to increased susceptibility and lymph node metastasis²². PARP-1 activation is involved in GC pathogenesis, especially through its interaction with Helicobacter pylori, which can stimulate PARP-1 activity and promote inflammatory responses that encourage tumor development^{23, 24}. Consequently, the use of PARP inhibitors as potential treatments for GC has become more appealing, as they may improve the efficacy of standard chemotherapies like cisplatin²⁵.

The PARP-1 gene, located on chromosome 1q41-42 and containing 23 exons, features the extensively studied SNP rs1136410 (Val762Ala)^{13, 26}. This SNP, resulting from a single nucleotide change that potentially alters PARP-1’s role in DNA repair and cancer-related processes, has been linked to cancer risk, particularly colorectal and GCs. Meta-analyses suggest a significant association between the rs1136410 C > T polymorphism and increased cancer susceptibility, especially in GC. The C allele is associated with increased risk for thyroid and cervical cancers, and decreased risk for brain cancer²⁷. The association with GC is particularly strong in East Asian populations^{27, 28}. However, conflicting results suggest that the rs1136410 polymorphism may be protective or exhibit no correlation in some demographics or cancer types²⁹, highlighting the complexity of genetic influences on cancer. These inconsistencies necessitate comprehensive meta-analyses to clarify genetic associations. This meta-analysis investigates the relationship between PARP-1 rs1136410 and CRC/GC risk, aiming to provide insights for patient risk assessment and management, especially in population-specific genetic counseling and precision medicine, and to establish evidence-based recommendations for incorporating genetic polymorphism data into clinical decision-making for gastrointestinal cancer prevention and early detection.

MATERIALS and METHODS

Literature Search and Database Selection

This systematic review and meta-analysis did not require ethical approval because it did not involve primary data collection from human subjects. A comprehensive literature search was conducted across multiple electronic databases through February 1, 2025, to ensure complete and up-to-date coverage of relevant studies examining the association between the PARP-1 rs1136410 polymorphism and CRC or GC risk, including both English and non-English publications. The databases searched included PubMed/MEDLINE, Scopus, EMBASE, Web of Science, Cochrane Library, BIOSIS Citation Index, LILACS, the Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, ProQuest Dissertations and Theses, Google Scholar, OpenGrey, and region-specific sources such as the China National Knowledge Infrastructure, Chinese Biomedical Database, Wan Fang Database, and VIP Information/Chinese Science and Technology Journal Database (VIP). The search strategy utilized a combination of Medical Subject Headings terms and free-text keywords, with cancer-related terms such as “colorectal cancer,” “gastric cancer,” “stomach cancer,” “colon cancer,” “rectal cancer,” “digestive tract cancer,” “gastrointestinal carcinoma,” “gastric neoplasm,” and “digestive system neoplasms”; PARP-1 related terms including “poly (ADP-ribose) polymerase 1,” “PARP-1,” “NAD+ ADP-ribosyltransferase 1,” “poly (ADP-ribose) synthase 1,” and “DNA repair enzyme”; and polymorphism-specific terms such as “rs1136410,” “Val762Ala,” “V762A,” “C>T,” “single nucleotide polymorphism,” “SNP,” “genotype,” “allele,” “mutation,” “variant,” and “genetic susceptibility.” Boolean operators (AND, OR, NOT), truncation, and proximity operators were applied to optimize retrieval. Reference lists of identified articles, relevant meta-analyses, and review papers were manually screened for additional studies. Ethical approval was not required for this systematic review and meta-analysis, as no primary data collection from human subjects was involved.

Study Selection Criteria

Studies were independently screened by two investigators using predefined inclusion and exclusion criteria. Inclusion criteria required: (1) case-control or cohort study design examining human subjects; (2) investigation of PARP-1 rs1136410 polymorphism association with CRC or GC risk; (3) availability of sufficient genotype frequency data to calculate odds ratios (ORs) and 95% confidence intervals (CIs); (4) clearly defined case and control populations with appropriate diagnostic criteria. Exclusion criteria eliminated: (1) animal studies, in vitro experiments, or cell line investigations; (2) studies lacking complete genotype frequency data; (3) family-based or linkage studies involving related individuals; (4) abstracts, case reports, editorials, reviews, conference proceedings, or meta-analyses; (5) duplicate publications or overlapping study populations. When multiple publications reported on the same study population, only the most recent or largest study was included to prevent data duplication.

Data Extraction and Management

Two independent reviewers extracted data using standardized forms, with disagreements resolved through discussion or consultation with a third reviewer when necessary. Extracted variables included first author name and publication year; study design and geographic location; participant ethnicity categorized as Asian, Caucasian, African, Hispanic, or mixed populations; total sample sizes for cases and controls; genotype frequencies for PARP-1 rs1136410 polymorphism in both cases and controls; genotyping methodology employed; Hardy-Weinberg equilibrium (HWE) test results in control groups; and minor allele frequencies in control groups. When data were unclear or missing, original study authors were contacted via email for clarification.

Quality Assessment

Study quality was evaluated using the Newcastle-Ottawa Scale (NOS), a validated tool for assessing the quality of non-randomized studies in meta-analyses^{30, 31}. The NOS evaluates three domains: selection of study groups (4 criteria), comparability of groups (1 criterion with 2 subcategories), and ascertainment of exposure or outcome (3 criteria). Each criterion awards one star except comparability, which can award up to two stars, resulting in a maximum score of nine stars. Studies scoring seven or more stars were classified as high quality, while those scoring five to six stars were considered of moderate quality and remained eligible for inclusion.

Statistical Analysis Methods

Meta-analysis was performed using Comprehensive Meta-Analysis software version 2.0. The association between PARP-1 rs1136410 polymorphism and cancer risk was assessed using ORs with 95% CIs under five genetic inheritance models: allele comparison (C vs. T), homozygous comparison (CC vs. TT), heterozygous comparison (CT vs. TT), dominant model (CC+CT vs. TT), and recessive model (CC vs. CT+TT). HWE in control groups was evaluated using Fisher’s exact test, with p-values <0.05 indicating deviation³². Between-study heterogeneity was assessed using Cochran’s Q statistic and quantified using the I² statistic, which describes the percentage of total variation across studies due to heterogeneity rather than chance. I² values of 25%, 50%, and 75% were interpreted as low, moderate, and high heterogeneity, respectively. When significant heterogeneity was detected (P<0.10 for Q statistic or I²>50%), a random-effects model using the DerSimonian-Laird method was employed; otherwise, a fixed-effects model using the Mantel-Haenszel method was applied^33-35. Predefined subgroup analyses were conducted by ethnicity, geographic region, control source (population-based vs. hospital-based), and genotyping method to explore potential sources of heterogeneity³⁶. Sensitivity analyses were performed by sequentially excluding individual studies to assess the robustness of pooled estimates. Publication bias was evaluated using Begg’s funnel plots and Egger’s linear regression test, with p<0.05 indicating significant bias. When publication bias was detected, the trim-and-fill method was applied to adjust pooled estimates. All statistical tests were two-sided with significance set at p<0.05.

RESULTS

Study Selection and Characteristics

As shown in Figure 1, the initial literature search identified 420 articles, which were reduced to 203 unique articles after removing duplicates. Title and abstract screening excluded 113 studies, leaving 90 for full-text review. Ultimately, 13 case-control studies met all eligibility criteria, comprising 3,591 cancer patients and 5,433 healthy controls. These included five CRC studies (1.807 cases, 2.912 controls) ^37-41 and eight GC studies (1.784 cases, 2.521 controls)^42-48. Table 1 shows the characteristics of selected studies. Published between 2004 and 2023, the studies represented global geographic distribution, including the United States, Singapore, China, Saudi Arabia, South Korea, and Brazil, and consisted predominantly of Asian (10 studies), with Caucasian (3 studies) and mixed ethnicity representation, reflecting cancer prevalence and enabling ethnic subgroup analyses. State-of-the-art genotyping methodologies were employed, including restriction fragment length polymorphism (RFLP)- polymerase chain reaction (PCR), TaqMan assays, SNaPshot sequencing, Illumina GoldenGate assays, Sequenom MassARRAY, and AS-PCR. The NOS indicated generally high study quality, but four GC studies (Miao⁴², Zhang⁴³, Wen⁴⁶, Tang²⁵) exhibited deviations from HWE (p<0.05), potentially impacting those analyses.

Quantitative Synthesis of Genetic Associations

Colorectal Cancer Risk Analysis

A meta-analysis of five studies investigating CRC risk found no significant overall association between the PARP-1 rs1136410 polymorphism and CRC risk across all genetic models (Table 2). However, ethnic stratification revealed significant population-specific differences. In Caucasian populations, the PARP-1 rs1136410 C allele demonstrated a significant protective effect against CRC development. The allele comparison model (C vs. T) showed a substantial risk reduction (OR=0.487, 95% CI 0.299-0.794, p=0.004), indicating that individuals carrying the C allele have approximately 51% lower odds of developing CRC compared to those with the T allele. This protective effect was consistent across multiple genetic models. Conversely, Asian populations exhibited a significantly increased CRC risk associated with the C allele. The allele comparison revealed a substantial risk elevation (C vs. T: OR=5.785, 95% CI 4.481-7.467, p≤0.001), indicating nearly six-fold increased odds of CRC development. The homozygous comparison (CC vs. TT: OR=1.413, 95% CI 1.094-1.824, p=0.008) and recessive model (CC vs. CT+TT: OR=1.302, 95% CI 1.040-1.629, p=0.021) further supported this increased risk pattern in Asian populations.

Gastric Cancer Risk Analysis

The meta-analysis of eight GC studies demonstrated consistent and statistically significant associations between the PARP-1 rs1136410 polymorphism and increased GC risk across multiple genetic inheritance models, providing robust evidence for genetic susceptibility to GC. The allele comparison model (C vs. T) showed a significant association with GC risk (OR=2.012, 95% CI 1.035-3.911, p=0.039), indicating that the C allele approximately doubles the odds of GC development (Figure 2A). The homozygous comparison (CC vs. TT) revealed an even stronger association (OR=1.766, 95% CI 1.239-2.515, p=0.002), suggesting that individuals homozygous for the C allele face nearly 77% increased odds of developing GC (Figure 2B). Heterozygous comparison (CT vs. TT: OR=1.359, 95% CI 1.180-1.565, p≤0.001) demonstrated significant risk elevation even in carriers of a single C allele (Figure 2C). The dominant model (CC+CT vs. TT: OR=0.649, 95% CI 0.455-0.927, p=0.017) (Figure 2D) and recessive model (CC vs. CT+TT: OR=1.541, 95% CI 1.079-2.200, p=0.017) (Figure 2E) provided additional evidence for the association. Ethnic subgroup analysis revealed that the association between PARP-1 rs1136410 polymorphism and GC risk was particularly pronounced in Asian populations, where the majority of included studies were conducted. This finding aligns with the known higher prevalence of GC in East Asian countries and suggests potential gene-environment interactions specific to these populations.

Heterogeneity Test

Heterogeneity analysis of the PARP-1 rs1136410 polymorphism showed variable inconsistency across genetic models and cancer types. In CRC, the C versus T genotype comparison exhibited high heterogeneity (I²=98.36%, pH ≤0.001), indicating significant variability in study outcomes. Moderate heterogeneity was observed for CC versus TT and CC+CT versus TT (I² = 54.43% and 48.29%, respectively), but the p-values did not indicate significant heterogeneity. Conversely, in the CT versus TT and CC versus CT+TT models, no heterogeneity was observed (I²=0.00%). In GC, substantial heterogeneity was also found for C versus T (I²=93.67%, p≤0.001) and CC versus TT (I²=61.65%, p=0.016), while CT versus TT showed no variability (I²=0.00%). Random effects models for specific comparisons in both CRC and GC revealed significant heterogeneity, especially among Asian populations, suggesting potential genetic or environmental influences on cancer risk across ethnicities. Overall, these heterogeneity findings highlight the complexity of interpreting associations between the PARP-1 rs1136410 polymorphism and cancer risk.

Sensitivity Analyses

The sensitivity analysis, conducted to evaluate the influence of individual studies on the meta-analysis of the PARP-1 rs1136410 polymorphism, demonstrated that no single study significantly altered the overall ORs across different genetic models, confirming the robustness of the findings. Exclusion of four studies deviating from HWE (Miao⁴², Zhang⁴³, Wen⁴⁶, and Tang²⁵) did not substantially change the pooled OR estimates. Specifically, for GC, after excluding the HWE-violating studies, significant associations were observed in the allele model (C vs. T: OR=1.89, 95% CI 1.12-3.21, p=0.018), homozygous model (CC vs. TT: OR=1.68, 95% CI 1.15-2.46, p=0.007), heterozygous model (CT vs. TT: OR=1.31, 95% CI 1.09-1.58, p=0.004), and recessive model (CC vs. CT+TT: OR=1.39, 95% CI 1.01-1.91, p=0.043), while the dominant model showed a borderline association (CC+CT vs. TT: OR=0.72, 95% CI 0.51-1.01, p=0.058). For CRC, all genetic models remained non-significant with effect sizes comparable to the main analysis, though ethnic-specific patterns -protective in Caucasians and risk-enhancing in Asians- persisted. Overall, these results reinforce the reliability of the meta-analysis conclusions and strengthen confidence in the observed association between the PARP-1 rs1136410 polymorphism and cancer susceptibility, thereby enhancing the credibility of the study.

Publication Bias

The assessment of publication bias for the PARP-1 rs1136410 polymorphism in relation to CRC and GC revealed varying results across different genetic models and ethnicities. Funnel plots (Figure 3A-E) indicate publication bias in the association between the PARP-1 rs1136410 polymorphism and the risks of CRC and GC. Begg’s and Egger’s tests indicated no significant publication bias for most genetic comparisons in CRC (p>0.05), including C vs. T, CC vs. TT, CT vs. TT, and CC+CT vs. TT models, and CC vs. CT+TT models (Begg’s p=0.806; Egger’s p=0.852). Similarly, among Asians, the C vs. T model showed no evidence of publication bias (Begg’s p=0.296; Egger’s p=0.138), while other comparisons exhibited limited variation, mostly indicating no bias (p≥0.050). For GC, assessment of publication bias also showed consistent results, with most comparisons displaying no significant bias, (C vs. T: Begg’s p=0.173; Egger’s p=0.472; CC vs. TT: Begg’s p=0.763; Egger’s p=0.752). These findings suggest a general absence of publication bias across the analyzed genetic models, reaffirming the robustness of the examined associations between the PARP-1 rs1136410 polymorphism and cancer risk.

DISCUSSION

This meta-analysis provides strong evidence for a link between the PARP-1 rs1136410 polymorphism and increased GC risk. This aligns with PARP-1’s role in gastric carcinogenesis. The C allele is associated with an approximate two-fold increase in GC odds (OR=2.012, 95% CI 1.035-3.911, p=0.039). Furthermore, individuals with two copies of the risk allele (CC vs. TT: OR=1.766, 95% CI 1.239-2.515, p=0.002) show a substantially elevated cancer susceptibility, suggesting a gene-dosage effect. Even a single copy of the variant allele (CT vs. TT: OR=1.359, 95% CI 1.180-1.565, p≤0.001) confers a measurable increased risk, indicating a dose-dependent influence on cancer development. The Val762Ala amino acid substitution encoded by rs1136410, located within the PARP-1 catalytic domain, may affect enzyme activity and DNA repair. In GC, where Helicobacter pylori infection causes chronic inflammation and DNA damage, altered PARP-1 function could impair cellular responses to genotoxic stress. Previous meta-analyses support this association, with Li et al.²⁶ suggesting a borderline significant increase in cancer risk associated with the C allele, particularly for GC. Qin et al.²⁸ found elevated risk for GC among Asian populations (OR=1.17, 95% CI 1.09-1.25). Hu et al.²⁹ also reported increased susceptibility to gastrointestinal cancers, especially within Asian populations.

In contrast to the GC findings, no overall association was found between the PARP-1 rs1136410 polymorphism and CRC risk. This difference may reflect fundamental distinctions in the molecular pathways driving colorectal versus gastric carcinogenesis. Factors like distinct embryological origins, tissue microenvironments, and mutational signatures could lead to varying selective pressures on DNA repair mechanisms. The multistep nature of colorectal carcinogenesis, involving specific genetic alterations such as Adenomatous Polyposis Coli mutations and microsatellite or chromosomal instability, might overshadow the impact of PARP-1 variants. Different roles of environmental factors in gastric and colorectal carcinogenesis may also modulate the penetrance of genetic susceptibility variants. The meta-analysis, encompassing five CRC studies (807 cases and 2.912 controls), provides sufficient statistical power to suggest that any association is likely small and clinically insignificant at the population level.

Ethnic Stratification and Population-Specific Risk Assessment

Ethnic stratification analysis reveals opposing effects of the PARP-1 rs1136410 polymorphism on CRC risk in Caucasian and Asian populations. In Caucasians, the C allele demonstrates a protective effect, with approximately 51% risk reduction (OR=0.487, 95% CI 0.299-0.794, p=0.004), while in Asians, it is associated with a six-fold increase in CRC odds, (OR=5.785, 95% CI 4.481-7.467, p≤0.001). These differences likely reflect complex interactions between the rs1136410 variant and population-specific genetic backgrounds, including linkage disequilibrium patterns, modifier gene allele frequencies, and distinct evolutionary histories. The magnitude of these ethnic differences necessitates a fundamental reconsideration of how genetic risk factors are incorporated into clinical practice and public health strategies. For Caucasian populations, individuals carrying the C allele of rs1136410 may warrant less intensive CRC screening, while Asian individuals carrying this variant may benefit from enhanced surveillance. However, the implementation of such ethnicity-specific recommendations requires careful consideration of factors such as the accuracy of self-reported ethnicity, the increasing prevalence of mixed-ancestry individuals, and the potential to exacerbate healthcare disparities. Future research should prioritize identifying causal variants and developing polygenic risk scores that account for population-specific effect sizes and allele frequencies.

Methodological and Geographic Considerations

This meta-analysis identified HWE deviations in nine of the included studies (p<0.05), indicating potential issues in study design, population stratification, or genotyping quality. While excluding these studies in sensitivity analyses did not significantly change the overall findings, the frequency of HWE deviations suggests a need for more rigorous quality control in future research. Significant heterogeneity across studies, addressed using random-effects models, reflects the complexity of genetic associations across diverse populations, study designs, and environmental contexts. Quality assessment using the NOS indicated predominantly high-quality studies,majority ≥7 stars, supporting the validity of the included research despite these challenges. Moreover, the global distribution of studies, including data from the United States, Singapore, China, Saudi Arabia, South Korea, and Brazil, strengthens the analysis by allowing for assessment of population-specific effects. However, the predominance of Asian studies (10 out of 13) may limit the generalizability of the findings and underscores the need for more research in underrepresented populations, particularly African and Hispanic populations. The temporal span of included studies (2004-2023) reflects advancements in genotyping technology, from RFLP-PCR to high-throughput platforms like TaqMan assays, Illumina GoldenGate, and Sequenom MassARRAY. The consistency of results across this technological timeline suggests that the observed associations represent genuine biological phenomena rather than platform-specific artifacts, although technological evolution likely contributes to some observed heterogeneity.

Clinical Implications and Translational Potential

This meta-analysis suggests that incorporating PARP-1 rs1136410 genotyping into personalized gastrointestinal cancer risk assessment is warranted. In GC, the consistent association with the C allele across multiple genetic models indicates its potential contribution to polygenic risk scores for stratified screening, particularly in high-risk individuals or those with additional risk factors. The observed two-fold increased risk with the C allele is clinically relevant and could influence screening recommendations. For CRC, ethnic-specific effects (protective in Caucasians, increased risk in Asians) offer opportunities for ancestry-specific risk stratification, but require careful implementation in diverse healthcare systems. Future research should focus on clinical decision support tools integrating genetic information, traditional risk factors, and ancestry-specific effect sizes. The association between PARP-1 rs1136410 and GC risk also has implications for PARP inhibitor therapy. Individuals with risk variants may exhibit differential responses due to altered baseline PARP-1 activity or dependencies on PARP-mediated DNA repair. Genotype-associated tumor characteristics may guide patient selection for PARP inhibitor monotherapy or combination therapy with chemotherapeutics like cisplatin. Understanding the functional consequences of the Val762Ala substitution may reveal mechanisms of PARP inhibitor resistance and sensitivity, informing the development of improved PARP inhibitors. Ethnic-specific effects suggest potential pharmacogenomic considerations for optimizing PARP inhibitor dosing across diverse populations.

Limitations and Future Research Directions

Despite the rigorous methodology applied in this meta-analysis, several limitations should be acknowledged. These include reliance on retrospective case-control studies that limit causal inference and introduce potential selection bias, and significant heterogeneity across included studies  likely reflects unmeasured confounders. Frequent deviations from HWE in control groups, particularly in GC studies, may suggest underlying biases, while the ethnic imbalance caused by the predominance of Asian populations constrains the generalizability of the findings. Additionally, variability in genotyping methods and incomplete adjustment for environmental exposures may have further influenced the results. Looking forward, future research should prioritize prospective cohort studies with robust phenotyping and environmental exposure assessment, alongside large-scale, multi-ethnic genome-wide association studies and polygenic risk scoring to improve predictive accuracy. Functional investigations are essential to clarify the biological consequences of the rs1136410 (Val762Ala) variant and its role in DNA repair, while Mendelian randomization could help establish causality. Integrating multi-omics approaches would provide a more comprehensive understanding of how PARP-1 variants contribute to disease susceptibility, while pharmacogenomic studies linking rs1136410 genotype with PARP inhibitor response in clinical trials could yield immediate translational relevance. Ultimately, the development of ancestry-informed genetic risk calculators incorporating multiple variants alongside clinical and environmental risk factors represents an important step toward advancing precision medicine.

CONCLUSION

This meta-analysis provides compelling evidence for cancer-type and ethnicity-specific associations between PARP-1 rs1136410 polymorphism and gastrointestinal cancer risk, with significant implications for personalized medicine approaches in oncology. The consistent association with increased GC risk across multiple genetic models, combined with the striking ethnic differences in CRC susceptibility, underscores the complexity of genetic influences on cancer development and the necessity of population-specific risk assessment strategies. These findings advance our understanding of the genetic architecture of gastrointestinal cancers and provide a foundation for developing more precise, ancestry-aware approaches to cancer screening, prevention, and treatment. Future research should focus on mechanistic studies, multi-ethnic validation, and clinical implementation strategies to translate these genetic insights into improved patient outcomes and population health benefits.