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. Author manuscript; available in PMC: 2026 Aug 25.
Published in final edited form as: Support Care Cancer. 2025 Apr 8;33(5):362. doi: 10.1007/s00520-025-09392-y

Pharmacogenomics of chemotherapy induced peripheral neuropathy using an electronic health record‑derived definition: a genome‑wide association study

Michael K Jones 1, Andrew Nicklawsky 2, Jonathan Shortt 3,7, Jack Pattee 4,7, Victoria Kennerley 3,7, Corbin J Eule 5, Nellowe Candelario 6; The Biobank at the Colorado Center for Personalized Medicine (Banner Authorship)7, Peter H O’Donnell 8, Thomas W Flaig 5
PMCID: PMC13502521  NIHMSID: NIHMS2195451  PMID: 40198382

Abstract

Purpose

Prior studies evaluating the genetic predisposition to chemotherapy induced peripheral neuropathy (CIPN) have been limited by small populations due to difficulty with real-world data extraction. This genome-wide association study (GWAS) evaluates the genetic differences between patients who developed CIPN against those unaffected, using an electronic health record (EHR) definition of CIPN.

Methods

This study included all patients who received chemotherapy associated with CIPN and had germline genetic data within the biobank at the Colorado Center for Personalized Medicine. CIPN was defined by a new neuropathic pain medication or an ICD-diagnosis of neuropathy after specified chemotherapy initiation. GWAS were stratified by (1) total population, (2) platinum chemotherapy, (3) taxane chemotherapy, and (4) vinca alkaloid chemotherapy. Genes previously associated with CIPN were analyzed within each GWAS.

Results

Nine hundred fifteen patients received chemotherapy associated with CIPN, with 528 patients (57%) developing CIPN. Median age at chemotherapy initiation was 60.5 years; female sex (n = 517, 56.5%) and White or Caucasian race (n = 822, 89.8%) were most common. Among single nucleotide polymorphisms (SNPs) that reached suggestive levels of genome-wide significance (p < 1 × 1 0−5), 60 SNPs occurred within 11 genes that may play a role in the development of or protection against CIPN, including RCOR1, CLDN14, TRIM5, and TMC2. No SNPs previously associated with CIPN achieved genome-wide significance in this population.

Conclusion

This pharmacogenomic study suggests several genomic loci that may modulate the development of CIPN. This EHR-definition may allow for increased sample sizes and improved statistical power in future genetic studies of CIPN.

Keywords: Pharmacogenomics, Chemotherapy-induced peripheral neuropathy, Electronic health record, Genome-wide association study, Personalized medicine

Introduction

The decision to proceed with chemotherapy is contingent upon an oncologist’s assessment of the patient’s likelihood to benefit and their capacity to tolerate the treatment’s adverse effects. Neuropathy is a common adverse effect of several frequently used chemotherapy agents, including the following medication classes: platinum analogues, taxanes, vinca alkaloids, thalidomide analogues, and proteasome inhibitors [1]. There are currently no effective medications to prevent chemotherapy-induced peripheral neuropathy (CIPN), which can develop into a chronic condition [2]. Interestingly, in the absence of pre-existing neuropathy, rates and severity of CIPN vary between patients, even with similar doses and medications. This suggests an underlying patient-specific and potential genetic difference that may play a role in developing CIPN [3].

Advances in pharmacogenomics within oncology have led to increased awareness of variation in medication metabolism for individual patients. Genetic variations in TPMT and NUDT15 are associated with higher rates of toxicity from thioguanine analogues (6-mercaptopurine, azathioprine) [4, 5]. DPYD codes for the enzyme that breaks down 5-fluorouracil in the liver, and deficiency in enzyme activity puts certain individuals at risk of severe toxicity [4]. Routine screening for germline mutations in DPYD is now the standard of care in Europe, but not in the USA [5].

Multiple studies have attempted to identify similar genomic or molecular predictors of CIPN, although with less consistent results. Several researchers have found varying pharmacogenomic predictors of platinum-induced neuropathy, including GSTP1, RPRD1B, MIDN, THEM5, and LIMCH1, but others did not confirm those variants [6–10]. Genes associated with taxane-induced neuropathy from prior analyses include FDG4, EPHA5, FZD3, VAC14,and GPR68 [11–13]. While some analyses, such as Khan et al. (2023), have included large populations, many of these studies have involved relatively small sample sizes, single types of cancer, single chemotherapy classes, or homogenous patient populations [6, 8, 10–16].

Due to the heterogeneity of results from prior studies, it is difficult to build and evaluate genetic risk prediction models for the development of CIPN, which limits the ability to create personalized treatment regimens for high-risk genotypes. In 2019, the Multinational Association of Supportive Care in Cancer (MASCC) published a comprehensive review of genomic predictors of CIPN. The report highlighted these challenges and called for “collaboration between study centers to increase sample size and confirm the generalizability of findings, and collaboration between patients, clinicians and translational researchers will support the application of innovative methods to address clinically meaningful outcomes” [3].

This GWAS used a novel, electronic health record (EHR)-derived definition of CIPN, paired with genetic data from our institution’s genetic biobank, to identify genetic predictors of CIPN in patients who received neurotoxic chemotherapy.

Methods

Study participants and neuropathy definition

Our study population was derived from consented participants of the biobank at the Colorado Center for Personalized Medicine (CCPM biobank) [17]. The CCPM biobank has genetic data from more than 70,000 patients across a large regional health system. All clinical variables used for inclusion/exclusion were extracted from the EHR. This project was approved by the Colorado Multiple Institutional Review Board.

We identified all patients within the CCPM biobank dataset who had received a chemotherapy agent known to be associated with CIPN: cisplatin, carboplatin, oxaliplatin, docetaxel, paclitaxel, cabazitaxel, vincristine, vinblastine, vinorelbine, lenalidomide, pomalidomide, bortezomib, carfilzomib, eribulin, ixabepilone, and enfortumab vedotin (Table 1). Patients were assessed as having CIPN (cases) by the following criteria: (1) ICD 9–10 diagnosis codes for neuropathy after treatment initiation (Appendix Table 1) or (2) prescribed a neuropathic pain medication after treatment initiation (Table 1).

Table 1:

Demographics and Clinical Characteristics of Study Population

Variables Values Case
(N = 528)		 Control
(N = 387)		 Overall
(N = 915)
Demographics
Age at Chemotherapy Initiation
(N, median, IQR)		 528
60.5
(50.4 – 67.6)		 387
60.6
(46.5 – 68.1)		 915
60.5
(49.4 – 67.8)
Sex Female (percent) 303 (57.4%) 214 (55.3%) 517 (56.5%)
Male 225 (42.6%) 173 (44.7%) 398 (43.5%)
Race White or Caucasian (percent 483 (91.5%) 339 (87.6%) 822 (89.8%)
Black or African American 11 (2.1%) 18 (4.7%) 29 (3.2%)
Asian 12 (2.3%) 7 (1.8%) 19 (2.1%)
American Indian or Alaska Native 1 (0.2%) 0 (0%) 1 (0.1%)
More than one Race 5 (1.0%) 4 (1.0%) 9 (1.0%)
Other 10 (1.9%) 10 (2.6%) 20 (2.2%)
Unknown 6 (1.1%) 9 (2.3%) 15 (1.6%)
Diagnosis and Treatment
Type of Cancer (N, percent)
Breast 161 (30.5%) 99 (25.7%) 260 (28.5%)
GI 171 (32.4%) 94 (24.4%) 265 (29.0%)
GU 122 (23.1%) 90 (23.3%) 212 (23.2%)
Gynecologic 86 (16.3%) 49 (12.7%) 135 (14.8%)
Head and Neck 39 (7.4%) 28 (7.3%) 67 (7.3%)
Hematologic Malignancy 145 (27.5%) 131 (33.9%) 276 (30.2%)
Lung 106 (20.1%) 63 (16.3%) 169 (18.5%)
Other cancer diagnoses 129 (24.4%) 110 (28.5%) 239 (26.2%)
Neuropathy Diagnosis (N, percent)
Diagnosis Code 293 (55.5%) - 293 (32.0%)
Antidepressants (amitriptyline, nortriptyline, venlafaxine, duloxetine) 109 (20.6%) - 109 (11.9%)
Gabapentinoids (pregabalin, gabapentin) 368 (69.7%) - 368 (40.2%)
Chemotherapy (N, percent)
Platinums 295 (55.9%) 192 (49.6%) 487 (53.2%)
Proteosome inhibitors 28 (5.3%) 24 (6.2%) 52 (5.7%)
Taxanes 244 (46.2%) 153 (39.5%) 397 (43.4%)
Thalidomide analogues 2 (0.4%) 1 (0.3%) 3 (0.3%)
Vinca alkaloids 54 (10.2%) 72 (18.6%) 126 (13.8%)
Others (eribulin, ixabepilone, enfortumab vedotin) 4 (0.8%) 1 (0.3%) 5 (0.6%)
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Available laboratory values were used to identify specific relevant conditions with respect to other causes of neuropathy. Patients with diabetes (hemoglobin A1c > 6.5%), hypothyroidism (TSH > 5.50 μIU/ml), or vitamin B12 deficiency (B12 < 200 pg/mL) were excluded [18, 19]. Patients who had been prescribed a neuropathic medication and had a confounding ICD diagnosis, such as mood disorders or migraines, were excluded to control for prior treatment with this class of medications (Appendix Table 1). Patients who received chemotherapy without meeting the prescribed CIPN criteria were designated as controls. Despite consenting to participate in the CCPM biobank, not all patients had genetic data available and were therefore excluded (Fig. 1).

Fig. 1.

Fig. 1

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Inclusion/exclusion diagram of total population. CCPM, The Biobank at the Colorado Center for Personalized Medicine

Genotyping and genome‑wide association study

Genotype data from CCPM biobank was generated in multiple batches on the Multi-Ethnic Genotyping Array (MEGA) or sequenced using the Twist Human Comprehensive Exome panel and the Twist Diversity SNP panel through a partnership with Regeneron Genetics Center, a subsidiary of Regeneron Pharmaceuticals. Imputation on the TOPMed Imputation Server using the TOPMed reference panel (r2) and imputation quality filtering were performed separately for data generated on different batches and platforms, and then imputed data was merged to create one dataset containing more than 46 M variants [20]. We performed a primary GWAS using REGENIE on the total population, as well as secondary GWAS using REGENIE on the following subsets: (1) patients who received platinum-based chemotherapy, (2) patients who received taxane-based chemotherapy, and (3) patients who received vinca alkaloid-based chemotherapy. All GWAS were performed with REGENIE software using bsize = 1000 and approximate Firth likelihood ratio test as fallback for p-values less than 0.01 [21]. Age, sex, the first ten genetic principal components, and genotyping batch were included as covariates. Rare variants (MAF < 0.01) and variants that failed a Hardy–Weinberg equilibrium test (p-value < 1 × 10−15) were removed before association testing. In accordance with similar studies in the field, the genome-wide significance threshold was set at < 5 × 10−8, and the threshold for suggestive of genome-wide significance was set at < 1 × 10−5 [22–24]. All logistic regression values (beta) were converted to odds ratios. Odds ratios referred to as > 1.0 or < 1.0 in the “Results” section indicate the 95% confidence intervals do not cross 1.0.

Annotation of SNPs was performed using the Ensembl Variant Effect Predictor (EVEP) and National Center of Biotechnology Information (NCBI) to identify if a SNP fell within a known gene boundary and into specific DNA elements such as intergenic variants, and intronic variants [25, 26].

Candidate gene analysis

In addition to the GWAS described above, we analyzed all SNPs within 50 kb pairs of 33 genes that have been previously associated with CIPN, based on recommendations from the MASCC Neurological Complications Working Group Overview of 2019 and other similar studies [3, 7, 11, 12, 14, 15] (Appendix Table 1).

Results

The CCPM biobank had genetic data available from 915 patients who received chemotherapy associated with CIPN. The median age at chemotherapy initiation was 60.5 years (IQR 49.4–67.8 years). Female sex (n = 517, 56.5%) and White or Caucasian race (n = 822, 89.8%) were predominant. Five hundred twenty-eight patients (57%) met the criteria for CIPN compared to 387 (43%) who did not (Table 1). CIPN was determined by ICD diagnosis codes (n = 293) and by prescription of neuropathic medication (n = 477) or both. The most common chemotherapy class received was platinum (n = 487, 53.2%), followed by taxane (n = 397, 43.4%), and vinca alkaloid (n = 126, 13.8%). The most common types of cancer under treatment were hematologic malignancies (n = 276, 30%), followed by gastrointestinal (n = 265, 29.0%) and breast (n = 260, 28.5%).

Genome‑wide association studies

Total population GWAS

The total population analysis did not identify any SNPs that reached genome-wide significance (p-value < 5 × 10−8, Fig. 2). Two hundred six SNPs were suggestive of genome-wide significance (p-value < 1 × 1 0−5 (Table 2). Of these, minor alleles at 104 SNPs were associated with development of CIPN (odds ratio (OR) > 1.0, 95% CI > 1.0), while minor alleles at 101 SNPs were associated with lower odds of CIPN (OR < 1.0, 95% CI < 1.0) (Table 2). SNPs suggestive of genome-wide significance were most commonly intergenic (n = 126, 61%) or intronic variants (n = 46, 22%). Sixty SNPs fell within 11 known genes based on genetic information from the EVEP and NCBI (Tables 2 and 3) [25, 26]. Three genes contained SNPs that all had OR > 1 (95% CI > 1.0), indicating the presence of a minor allele was associated with developing CIPN. Eight genes contained SNPs that all had OR < 1 (95% CI < 1.0), indicating the presence of a minor allele was associated with a lower risk of developing CIPN (Tables 2 and 3).

Fig. 2.

Fig. 2

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A Manhattan plot of common variant SNPs (minor allele frequency > 0.05) for all study patients, with red line representing genome-wide significance (p < 5 × 10−8) and blue line suggestive of genome-wide significance (p < 1 × 10−5). B QQ plot of GWAS of all study patients

Table 2:

SNPs suggestive of genome wide significance, of all patients in study population and platinum subset only (denoted by *). Ranked by lowest p-values.

CHROMOSOME GENE POSITION SNP ALLELE 0 ALLELE 1 ALLELE 1 FREQUENCY BETA ODDS RATIO LOWER 95% CI UPPER 95% CI P-VALUE GENE SNP FALLS WITHIN SNP CATEGORY
13 111502600 rs1888305 C T 30% −0.6061 0.55 0.43 0.70 7.78E-07 Intergenic Variant
13 111502515 rs1888306 C T 30% −0.6061 0.55 0.43 0.70 7.78E-07 Intergenic Variant
13 111501966 rs2528783 A C 30% −0.6061 0.55 0.43 0.70 7.78E-07 Intergenic Variant
13 111503048 rs2774443 G C 30% −0.5939 0.55 0.43 0.70 1.28E-06 Intergenic Variant
4 175205838 rs73875514 C G 10% 0.9892 2.69 1.78 4.06 1.36E-06 Intronic Variant, Non-Coding Transcript Variant
13 111503205 rs2528781 T C 30% −0.5926 0.55 0.43 0.70 1.36E-06 Intergenic Variant
2 175236934 rs6721193 G T 10% −0.8696 0.42 0.29 0.60 1.91E-06 Intergenic Variant
2 175231762 rs4972464 G T 9% −0.9306 0.39 0.27 0.58 1.95E-06 Intergenic Variant
13 111498586 rs56276945 C CT 30% −0.5810 0.56 0.44 0.71 1.99E-06 Intergenic Variant
11 69630892 rs79605071 C T 9% −0.9362 0.39 0.26 0.58 2.06E-06 Intergenic Variant
2 175241941 rs35217812 CTTTG C 10% −0.8698 0.42 0.29 0.60 2.06E-06 Intergenic Variant
12 131099551 rs35453516 G A 13% −0.7717 0.46 0.33 0.64 2.44E-06 ADGRD1 Intronic Variant
9 135237182 rs4842231 C A 32% −0.5368 0.58 0.47 0.73 2.46E-06 Intronic Variant, Non-Coding Transcript Variant
11 91588600 rs11019564 T G 46% 0.5182 1.68 1.35 2.09 2.54E-06 Intergenic Variant
14 102684707 rs5811079 T TG 12% −0.7955 0.45 0.32 0.63 2.56E-06 RCOR1 Intronic Variant
13 111496751 rs14064098 C T 30% −0.5747 0.56 0.44 0.72 2.72E-06 Intergenic Variant
13 111496540 rs9588452 G C 30% −0.5747 0.56 0.44 0.72 2.72E-06 Intergenic Variant
11 91591591 rs4753341 G A 46% 0.5163 1.68 1.35 2.08 2.73E-06 Intergenic Variant
7 101086185 rs73178512 G A 11% −0.8079 0.45 0.32 0.63 2.74E-06 TRIM56 Intronic Variant
2 175240338 rs13383543 C T 10% −0.8584 0.42 0.30 0.61 2.84E-06 Intergenic Variant
2 175240169 rs4578824 C T 10% −0.8584 0.42 0.30 0.61 2.84E-06 Regulatory Region Variant
2 175239543 rs6758379 A G 10% −0.8584 0.42 0.30 0.61 2.84E-06 Intergenic Variant
14 102698808 rs78142501 G C 12% −0.7927 0.45 0.32 0.63 2.87E-06 RCOR1 Intronic Variant
7 101079139 rs13232139 G A 10% −0.8378 0.43 0.30 0.62 2.89E-06 Intergenic Variant
12 131099059 rs12818313 A G 13% −0.7667 0.46 0.34 0.64 2.92E-06 ADGRD1 Intronic Variant
13 111500362 rs2528784 C T 31% −0.5700 0.57 0.44 0.72 2.98E-06 Intergenic Variant
2 175242487 rs6741968 G T 10% −0.8595 0.42 0.29 0.61 2.99E-06 Intergenic Variant
2 175238456 rs10206628 G A 10% −0.8545 0.43 0.30 0.61 3.15E-06 Intergenic Variant
14 102747515 rs76582128 C T 12% −0.7710 0.46 0.33 0.64 3.23E-06 Intergenic Variant
11 91581660 rs11019551 C T 45% 0.5168 1.68 1.35 2.09 3.27E-06 Intergenic Variant
7 101093687 rs148938283 G A 11% −0.8028 0.45 0.32 0.63 3.33E-06 TRIM56 3_Prime_Utr Variant
12 131095433 rs34982748 G A 13% −0.7622 0.47 0.34 0.65 3.37E-06 ADGRD1 Intronic Variant
14 102747703 rs4906256 G A 13% −0.7414 0.48 0.35 0.65 3.39E-06 Intergenic Variant
11 91579987 rs12806872 G A 45% 0.5147 1.67 1.34 2.08 3.50E-06 Intergenic Variant
11 91568295 rs10830754 T C 45% 0.5141 1.67 1.34 2.08 3.59E-06 Intergenic Variant
11 91568253 rs1125760 T C 45% 0.5141 1.67 1.34 2.08 3.59E-06 Intergenic Variant
11 91571324 rs11019537 A T 45% 0.5130 1.67 1.34 2.08 3.62E-06 Intergenic Variant
14 102621535 rs4906244 C T 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
14 102606336 rs149460194 A G 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
14 102673421 rs141334183 C T 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
14 102654727 rs116256454 A T 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
14 102642730 rs115383443 G A 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
14 102594081 rs79271450 C T 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
14 102595834 rs4900547 C G 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
14 102601370 rs60300877 C A 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
14 102603744 rs77952079 C T 12% −0.7822 0.46 0.33 0.64 3.62E-06 RCOR1 Intronic Variant
11 91572935 rs2514277 T C 45% 0.5136 1.67 1.34 2.08 3.63E-06 Intergenic Variant
11 91575724 rs11404746 CT C 45% 0.5134 1.67 1.34 2.08 3.66E-06 Intergenic Variant
11 91568388 rs1125761 A G 45% 0.5135 1.67 1.34 2.08 3.68E-06 Intergenic Variant
11 91567745 rs1400994 C T 45% 0.5135 1.67 1.34 2.08 3.68E-06 Intergenic Variant
11 91568007 rs1980209 T C 45% 0.5135 1.67 1.34 2.08 3.68E-06 Intergenic Variant
11 91568435 rs2459880 G A 45% 0.5135 1.67 1.34 2.08 3.68E-06 Intergenic Variant
9 135249108 rs14149986 G GCCTT 40% −0.5312 0.59 0.47 0.74 3.69E-06 Intronic Variant, Non-Coding Transcript Variant
11 91575535 rs1022362 T C 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91575366 rs1022363 T C 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91571975 rs11019538 C T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91571754 rs11602247 G A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91577591 rs14217047 C CA 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91574004 rs1518126 T C 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91570818 rs1518136 G C 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91571044 rs1518137 A G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91571176 rs1518138 T C 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91572469 rs2459860 A T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91572692 rs2459861 G A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91577422 rs2459864 A G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91577350 rs2459865 C T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91575599 rs2459868 A G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91575442 rs2459869 G A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91569493 rs2459884 C A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91569575 rs2459885 A G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91569975 rs2459887 G T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91569304 rs2514272 C T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91570636 rs2514273 G A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91571502 rs2514274 G A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91572553 rs2514275 T A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91572786 rs2514276 T C 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91573015 rs2514278 C T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91573044 rs2514279 T G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91573070 rs2514280 A G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91573145 rs2514281 A G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91573857 rs2514286 A G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91575693 rs2514289 G A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91576258 rs2514290 T C 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91576389 rs2514291 A G 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91576615 rs2514292 G A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91577459 rs2514295 C T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91577698 rs2514296 C T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91574421 rs66533610 AT A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91577800 rs7394706 C A 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91578144 rs7395014 A T 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91578141 rs7396040 G C 45% 0.5129 1.67 1.34 2.08 3.72E-06 Intergenic Variant
11 91581717 rs11019552 G A 45% 0.5145 1.67 1.34 2.08 3.73E-06 Intergenic Variant
11 91581727 rs11019553 T C 45% 0.5145 1.67 1.34 2.08 3.73E-06 Intergenic Variant
11 91580672 rs11529021 T A 45% 0.5145 1.67 1.34 2.08 3.73E-06 Intergenic Variant
11 91581779 rs2514266 A G 45% 0.5145 1.67 1.34 2.08 3.73E-06 Intergenic Variant
11 91581834 rs2514267 T A 45% 0.5145 1.67 1.34 2.08 3.73E-06 Intergenic Variant
11 91573395 rs2514282 T G 45% 0.5125 1.67 1.34 2.08 3.79E-06 Intergenic Variant
11 91580509 rs12224291 G A 45% 0.5125 1.67 1.34 2.08 3.79E-06 Intergenic Variant
11 91580065 rs12575907 C A 45% 0.5125 1.67 1.34 2.08 3.79E-06 Intergenic Variant
11 91580174 rs12576183 C T 45% 0.5125 1.67 1.34 2.08 3.79E-06 Intergenic Variant
7 101107973 rs73178519 C T 11% −0.7908 0.45 0.32 0.64 3.90E-06 Intergenic Variant
14 102712370 rs150582451 A G 12% −0.7747 0.46 0.33 0.64 3.94E-06 RCOR1 Intronic Variant
14 102750014 rs4900553 T C 14% −0.7290 0.48 0.35 0.66 3.96E-06 Regulatory Region Variant
14 102749655 rs4906257 C A 14% −0.7290 0.48 0.35 0.66 3.96E-06 Regulatory Region Variant
14 102750064 rs61152564 G T 14% −0.7290 0.48 0.35 0.66 3.96E-06 Regulatory Region Variant
14 102750066 rs61281821 A G 14% −0.7290 0.48 0.35 0.66 3.96E-06 Regulatory Region Variant
11 91577063 rs14633681 T C 45% 0.5118 1.67 1.34 2.08 3.97E-06 Intergenic Variant
2 175231641 rs4972463 T C 9% −0.8949 0.41 0.28 0.60 4.25E-06 Intergenic Variant
11 91597513 rs2379023 G A 47% 0.5094 1.66 1.34 2.07 4.38E-06 Intergenic Variant
14 102636744 rs146580675 C T 12% −0.7752 0.46 0.33 0.64 4.40E-06 RCOR1 Intronic Variant
21 36512938 rs9975228 G A 21% −0.6279 0.53 0.41 0.70 4.43E-06 CLDN14 Intronic Variant
11 91583335 rs11019557 A G 46% 0.5127 1.67 1.34 2.08 4.45E-06 Intergenic Variant
7 101080613 rs28651567 C T 12% −0.7686 0.46 0.33 0.65 4.55E-06 TRIM56 Upstream Gene Variant
7 101081171 rs7786422 C T 12% −0.7686 0.46 0.33 0.65 4.55E-06 TRIM56 Upstream Gene Variant
14 102748897 rs4900551 T C 14% −0.7248 0.48 0.35 0.66 4.61E-06 Intergenic Variant
14 102750750 rs4906258 T G 12% −0.7706 0.46 0.33 0.64 4.65E-06 Intergenic Variant
14 102697644 rs139019675 T TC 12% −0.7583 0.47 0.34 0.65 4.65E-06 RCOR1 Intronic Variant
18 9309384 rs54697684 C CA 4% −1.2974 0.27 0.15 0.49 4.69E-06 Downstream Gene Variant
7 101070694 rs73178503 C A 11% −0.7758 0.46 0.33 0.65 4.77E-06 Intergenic Variant
14 102726999 rs75017083 C T 12% −0.7667 0.46 0.33 0.65 4.80E-06 RCOR1 3_Prime_Utr Variant
7 101051857 rs73168398 G A 11% −0.7854 0.46 0.32 0.64 4.93E-06 MUC17 Missense Variant
14 102612352 rs115494013 C T 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
14 102639870 rs114846369 C T 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
14 102601078 rs149821483 A G 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
14 102643963 rs114213158 T A 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
14 102644025 rs74810174 A G 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
14 102650261 rs4900548 C T 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
14 102599305 rs78475547 A G 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
14 102657945 rs116780532 G A 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
14 102671861 rs4633650 C G 12% −0.7646 0.47 0.33 0.65 4.93E-06 RCOR1 Intronic Variant
7 101072593 rs9792109 G A 10% −0.7930 0.45 0.32 0.64 4.98E-06 Intergenic Variant
7 101076427 rs11566678 C A 11% −0.7749 0.46 0.33 0.65 5.05E-06 Intergenic Variant
11 91578837 rs67929165 T A 45% 0.5059 1.66 1.33 2.07 5.14E-06 Intergenic Variant
18 78140225 rs12965943 T G 24% 0.6023 1.83 1.40 2.38 5.15E-06 Non-Coding Transcript Exon Variant
11 91580577 rs11525329 A C 45% 0.5055 1.66 1.33 2.07 5.23E-06 Intergenic Variant
11 91580591 rs12225550 C G 45% 0.5055 1.66 1.33 2.07 5.23E-06 Intergenic Variant
11 91580339 rs12577086 A G 45% 0.5055 1.66 1.33 2.07 5.23E-06 Intergenic Variant
11 91580292 rs12788357 G A 45% 0.5055 1.66 1.33 2.07 5.23E-06 Intergenic Variant
11 91580440 rs15121244 CA C 45% 0.5055 1.66 1.33 2.07 5.23E-06 Intergenic Variant
14 102603675 rs116792245 C T 12% −0.7699 0.46 0.33 0.65 5.24E-06 RCOR1 Intronic Variant
12 131092111 rs34255965 G A 13% −0.7452 0.47 0.34 0.66 5.31E-06 ADGRD1 Intronic Variant
12 131092085 rs34507968 A G 13% −0.7452 0.47 0.34 0.66 5.31E-06 ADGRD1 Intronic Variant
12 131093066 rs67818722 C T 13% −0.7452 0.47 0.34 0.66 5.31E-06 ADGRD1 Intronic Variant
14 102749516 rs4900552 C T 12% −0.7658 0.46 0.33 0.65 5.50E-06 Regulatory Region Variant
11 91578783 rs74535422 G T 45% 0.5032 1.65 1.33 2.06 5.77E-06 Intergenic Variant
12 131089548 rs34096738 C T 13% −0.7348 0.48 0.35 0.66 5.83E-06 ADGRD1 Intronic Variant
12 131089230 rs61939673 G A 13% −0.7348 0.48 0.35 0.66 5.83E-06 ADGRD1 Intronic Variant
11 91578462 rs61915465 T C 45% 0.5034 1.65 1.33 2.06 5.89E-06 Intergenic Variant
11 91592505 rs3899377 A G 47% 0.5027 1.65 1.33 2.06 6.01E-06 Intergenic Variant
14 102701751 rs77380526 G A 12% −0.7777 0.46 0.33 0.64 6.13E-06 RCOR1 Intronic Variant
11 91570564 rs10765485 A G 46% 0.5039 1.66 1.33 2.06 6.15E-06 Intergenic Variant
14 102591298 rs4906230 C T 12% −0.7497 0.47 0.34 0.66 6.16E-06 RCOR1 Upstream Gene Variant
14 102591730 rs78711800 G C 12% −0.7497 0.47 0.34 0.66 6.16E-06 RCOR1 Upstream Gene Variant
14 102591979 rs8009380 G C 12% −0.7497 0.47 0.34 0.66 6.16E-06 RCOR1 Upstream Gene Variant
11 91580070 rs2397699 A G 46% 0.5036 1.65 1.33 2.06 6.24E-06 Intergenic Variant
11 91590070 rs34139243 A AT 47% 0.5015 1.65 1.33 2.06 6.26E-06 Intergenic Variant
11 91578809 rs77373275 A T 45% 0.5010 1.65 1.33 2.06 6.36E-06 Intergenic Variant
7 101064828 rs73170203 C T 11% −0.7634 0.47 0.33 0.65 6.38E-06 Intergenic Variant
11 91578822 rs77037457 T C 45% 0.5003 1.65 1.32 2.05 6.54E-06 Intergenic Variant
2 131806368 rs34034097 A AT 10% 0.8408 2.32 1.59 3.39 6.67E-06 CDRT15P3 Upstream Gene Variant
11 91580129 rs71062035 C CA 45% 0.4999 1.65 1.32 2.05 6.72E-06 Intergenic Variant
18 78141055 rs8088204 C T 24% 0.5954 1.81 1.39 2.36 6.96E-06 Downstream Gene Variant
9 135247961 rs2298246 G A 35% −0.5153 0.60 0.48 0.75 7.05E-06 Intronic Variant, Non-Coding Transcript Variant
7 101054606 rs35802441 A T 11% −0.7476 0.47 0.34 0.66 7.31E-06 MUC17 Intronic Variant
14 102735538 rs74084153 A G 14% −0.7080 0.49 0.36 0.67 7.36E-06 RCOR1 Downstream Gene Variant
14 102740979 rs60903095 C T 12% −0.7620 0.47 0.33 0.65 7.37E-06 Intergenic Variant
18 78142067 rs55634452 A G 24% 0.5889 1.80 1.39 2.34 7.37E-06 Downstream Gene Variant
18 78140770 rs924889 A G 24% 0.5889 1.80 1.39 2.34 7.37E-06 Non-Coding Transcript Exon Variant
21 28231304 rs429864 A G 21% −0.6057 0.55 0.42 0.71 7.39E-06 LINC01695 Upstream Gene Variant
5 25035490 rs72755809 C T 28% 0.5559 1.74 1.36 2.23 7.68E-06 Intergenic Variant
18 9111648 rs141232585 C T 3% −1.4334 0.24 0.12 0.46 7.82E-06 NDUFV2 Intronic Variant
14 102708876 rs80031694 G C 12% −0.7512 0.47 0.34 0.66 7.83E-06 RCOR1 Intronic Variant
11 91594398 rs10830757 T C 47% 0.4973 1.64 1.32 2.05 7.89E-06 Intergenic Variant
7 5823017 rs2287589 G A 23% −0.5631 0.57 0.44 0.73 7.99E-06 ZNF815P Upstream Gene Variant
11 91572654 rs11019539 T C 46% 0.4990 1.65 1.32 2.05 8.08E-06 Intergenic Variant
11 91581507 rs13952991 T C 46% 0.5004 1.65 1.32 2.06 8.13E-06 Intergenic Variant
14 102743934 rs14466306 A G 14% −0.7057 0.49 0.36 0.67 8.19E-06 Intergenic Variant
18 78152243 rs35084996 T A 24% 0.5800 1.79 1.38 2.31 8.21E-06 Intergenic Variant
18 78140192 rs12957925 G A 24% 0.5870 1.80 1.38 2.34 8.36E-06 Non-Coding Transcript Exon Variant
12 131083583 rs12810812 C T 12% −0.7373 0.48 0.34 0.66 8.36E-06 ADGRD1 Intronic Variant
11 91590106 rs3908111 G T 47% 0.4955 1.64 1.32 2.05 8.40E-06 Intergenic Variant
20 2638548 rs36029032 CAGA C 9% 0.8868 2.43 1.62 3.65 8.48E-06 TMC2 Intronic Variant
18 78139991 rs36084769 C T 24% 0.5909 1.81 1.39 2.35 8.49E-06 Non-Coding Transcript Exon Variant
14 102747239 rs4906255 C T 12% −0.7499 0.47 0.34 0.66 8.59E-06 Intergenic Variant
11 91602319 rs35107699 T TA 47% 0.4968 1.64 1.32 2.05 8.68E-06 Intergenic Variant
21 28248050 rs118736 G A 21% −0.5975 0.55 0.42 0.72 8.83E-06 Intergenic Variant
21 28247396 rs118737 T C 21% −0.5975 0.55 0.42 0.72 8.83E-06 Intergenic Variant
21 28247784 rs3053319 A AGTT 21% −0.5975 0.55 0.42 0.72 8.83E-06 Intergenic Variant
21 28249473 rs391427 T C 21% −0.5975 0.55 0.42 0.72 8.83E-06 Intergenic Variant
1 91762933 rs11334581 TC T 43% 0.4817 1.62 1.31 2.01 8.92E-06 TGFBR3 Intronic Variant
14 102750955 rs60714848 C T 12% −0.7357 0.48 0.35 0.66 8.95E-06 Intergenic Variant
14 102728661 rs8006699 A G 18% −0.6223 0.54 0.41 0.71 9.05E-06 RCOR1 3_Prime_Utr Variant
20 2616116 rs6050622 G A 10% 0.8401 2.32 1.58 3.40 9.15E-06 TMC2 Intronic Variant
18 78153505 rs35322659 C T 23% 0.5942 1.81 1.39 2.37 9.25E-06 Intergenic Variant
18 63114979 rs2086466 G A 37% −0.5357 0.59 0.46 0.74 9.36E-06 Intergenic Variant
18 78147694 rs7237276 C T 24% 0.5704 1.77 1.37 2.29 9.63E-06 Intergenic Variant
14 102724506 rs59457020 A G 13% −0.7282 0.48 0.35 0.67 9.65E-06 RCOR1 Intronic Variant
18 78140912 rs924887 G C 24% 0.5793 1.78 1.38 2.32 9.71E-06 Downstream Gene Variant
18 78140840 rs924888 G A 24% 0.5793 1.78 1.38 2.32 9.71E-06 Non-Coding Transcript Exon Variant
11 91561007 rs11019527 C T 46% 0.4954 1.64 1.32 2.05 9.73E-06 Intergenic Variant
20 2619294 rs1028442 C A 9% 0.8941 2.45 1.62 3.69 9.76E-06 TMC2 Intronic Variant
20 2617759 rs13040075 G A 9% 0.8941 2.45 1.62 3.69 9.76E-06 TMC2 Intronic Variant
18 78151987 rs35648462 G A 24% 0.5779 1.78 1.37 2.31 9.93E-06 Intergenic Variant
21 28229634 rs452763 G C 21% −0.5943 0.55 0.42 0.72 9.94E-06 LINC01695 Upstream Gene Variant
12 131083684 rs12811004 C T 12% −0.7300 0.48 0.35 0.67 9.96E-06 ADGRD1 Intronic Variant
17* 68284941 rs11869470 C T 40% −1.1268 0.32 0.21 0.50 1.63E-07 SLC16A6 Intronic Variant
17* 68287047 rs7212016 G A 40% −1.1268 0.32 0.21 0.50 1.63E-07 SLC16A6 Intronic Variant
17* 68286010 rs2041129 T C 39% −1.0955 0.33 0.22 0.52 4.60E-07 SLC16A6 Intronic Variant
17* 68286614 rs6501351 C T 39% −1.0955 0.33 0.22 0.52 4.60E-07 SLC16A6 Intronic Variant
17* 68289252 rs2190760 C G 39% −1.0955 0.33 0.22 0.52 4.60E-07 SLC16A6 Intronic Variant
6* 9767853 rs2327201 G C 27% −1.0589 0.35 0.23 0.53 1.26E-06 OFCC1 Intronic Variant, Non-Coding Transcript Variant
6* 9767851 rs201192390 TA T 27% −1.0589 0.35 0.23 0.53 1.26E-06 OFCC1 Intronic Variant, Non-Coding Transcript Variant
3* 196824767 rs6583179 C G 40% 0.9525 2.59 1.73 3.89 1.78E-06 PAK2 Intronic Variant
8* 143470548 rs76578854 G A 9% −1.6555 0.19 0.09 0.39 2.65E-06 ZC3H3 Intronic Variant
6* 9768138 rs2092093 C T 27% −1.0273 0.36 0.23 0.55 3.12E-06 OFCC1 Intronic Variant, Non-Coding Transcript Variant
3* 196819658 rs10446497 T G 39% 0.9391 2.56 1.70 3.85 3.32E-06 PAK2 Intronic Variant
1* 94652759 rs6660609 G A 9% 1.8099 6.11 2.61 14.29 3.61E-06 KATNBL1P2 Upstream Gene Variant
7* 110283153 rs67579037 C T 19% −1.2177 0.30 0.18 0.50 3.90E-06 Intronic Variant, Non-Coding Transcript Variant
7* 27300282 rs17438159 A G 15% −1.2604 0.28 0.17 0.48 4.05E-06 Regulatory Region Variant
7* 110281830 rs66805126 G A 19% −1.2062 0.30 0.18 0.50 4.68E-06 Intronic Variant, Non-Coding Transcript Variant
7* 110271279 rs12671447 T A 19% −1.1912 0.30 0.18 0.51 6.21E-06 Intronic Variant, Non-Coding Transcript Variant
7* 110271638 rs10487317 G A 19% −1.1853 0.31 0.18 0.51 6.62E-06 Intronic Variant, Non-Coding Transcript Variant
1* 56330183 rs3005913 A G 27% −0.9843 0.37 0.24 0.58 7.03E-06 Intronic Variant, Non-Coding Transcript Variant
17* 68292900 rs3760269 G T 41% −0.9474 0.39 0.26 0.59 7.09E-06 SLC16A6 Upstream Gene Variant
17* 68290996 rs1319198 C A 40% −0.9617 0.38 0.25 0.59 7.82E-06 SLC16A6 Intronic Variant
11* 134699208 rs12277397 G T 12% 1.4166 4.12 2.13 7.98 7.90E-06 Intronic Variant, Non-Coding Transcript Variant
8* 143452182 rs72691428 G A 9% −1.5735 0.21 0.10 0.42 7.93E-06 ZC3H3 Intronic Variant
11* 134701041 rs11223958 C T 11% 1.4161 4.12 2.13 7.98 8.27E-06 Intronic Variant, Non-Coding Transcript Variant
7* 110282523 rs67805305 G C 18% −1.1991 0.30 0.18 0.51 8.46E-06 Intronic Variant, Non-Coding Transcript Variant
11* 134724368 rs73600945 T C 11% 1.4362 4.20 2.16 8.19 8.62E-06 Intergenic Variant
17* 68290916 rs5821650 C CCTAA 41% −0.9403 0.39 0.26 0.59 8.79E-06 SLC16A6 Intronic Variant
8* 143451955 rs72691427 G A 9% −1.5865 0.20 0.10 0.42 9.34E-06 ZC3H3 Intronic Variant
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Table 3:

Genes that SNPs suggestive of genome wide significance fell within, from total study population and platinum subset only (marked by *). Odds ratios included from SNPs with lowest P-values within each gene. Name and function included from National Center for Biotechnology Information.

Gene (Odds Ratio) Name Description
TMC2 (OR = 2.45) Transmembrane channel like 2 This gene encodes a transmembrane protein that is necesssary for mechanotransduction in cochlear hair cells of the inner ear. Mutations in this gene may underlie hereditary disorders of balance and hearing
CDRT15P3 (OR = 2.32) CDRT15 pseudogene 3 Unknown function. Broad expression in testis (RPKM 1.2), brain (RPKM 0.8).
TGFBR3 (OR = 1.62) transforming growth factor beta receptor 3 This locus encodes the transforming growth factor (TGF)-beta type III receptor. The encoded receptor is a membrane proteoglycan that often functions as a co-receptor with other TGF-beta receptor superfamily members. Ectodomain shedding produces soluble TGFBR3, which may inhibit TGFB signaling. Decreased expression of this receptor has been observed in various cancers. Alternatively spliced transcript variants encoding different isoforms have been identified for this gene.
ZNF815P (OR = 0.57) zinc finger protein 815, pseudogene Unknown function. Ubiquitous expression in brain (RPKM 2.1), appendix (RPKM 1.2), lymph nodes (RPKM 1.2), spleen (RPKM 1.1), and testis (RPKM 1.1)
LINC01695 (OR = 0.55) long intergenic non-protein coding RNA 1695 Unknown function. Low expression in observed datasets.
RCOR1 (OR = 0.45) REST corepressor 1 This gene encodes a protein that is well-conserved, downregulated at birth, and with a specific role in determining neural cell differentiation. The encoded protein binds to the C-terminal domain of REST (repressor element-1 silencing transcription factor). Ubiquitous expression in bone marrow (RPKM 19.5), esophagus (RPKM 14.2) and other tissues.
CLDN14 (OR = 0.53) Claudin 14 Tight junctions represent one mode of cell-to-cell adhesion in epithelial or endothelial cell sheets, forming continuous seals around cells and serving as a physical barrier to prevent solutes and water from passing freely through the paracellular space. These junctions are comprised of sets of continuous networking strands in the outwardly facing cytoplasmic leaflet, with complementary grooves in the inwardly facing extracytoplasmic leaflet. The protein encoded by this gene, a member of the claudin family, is an integral membrane protein and a component of tight junction strands. Defects in this gene are the cause of an autosomal recessive form of nonsyndromic sensorineural deafness. It is also reported that four synonymous variants in this gene are associated with kidney stones and reduced bone mineral density.
ADGRD1 (OR = 0.46) adhesion G protein-coupled receptor D1 The adhesion G-protein-coupled receptors (GPCRs), including GPR133, are membrane-bound proteins with long N termini containing multiple domains. GPCRs, or GPRs, contain 7 transmembrane domains and transduce extracellular signals through heterotrimeric G proteins.
MUC17 (OR = 0.46) mucin 17, cell surface associated The protein encoded by this gene is a membrane-bound mucin that provides protection to gut epithelial cells.
TRIM56 (OR = 0.45) tripartite motif containing 56 Enables RNA binding activity. Predicted to be involved in several processes, including defense response to other organism; positive regulation of macromolecule metabolic process; and protein K63-linked ubiquitination. Predicted to be located in cytoplasm. Predicted to be active in chromatin and nucleoplasm.
NDUFV2 (0.24) NADH:ubiquinone oxidoreductase core subunit V2 The NADH-ubiquinone oxidoreductase complex (complex I) of the mitochondrial respiratory chain catalyzes the transfer of electrons from NADH to ubiquinone. The complex is located in the inner mitochondrial membrane. Mutations in this gene are implicated in Parkinson's disease, bipolar disorder, schizophrenia, and have been found in one case of early onset hypertrophic cardiomyopathy and encephalopathy. A non-transcribed pseudogene of this locus is found on chromosome 19.
KATNBL1P2* (OR = 6.11) Katanin regulatory subunit B1 like 1 pseudogene 2 Unknown function.
OFCC1* (OR = 0.35) Orofacial cleft 1 candidate 1 Predicted to be located in cytosol; endoplasmic reticulum; and microtubule cytoskeleton. Predicted to be active in perinuclear region of cytoplasm.
PAK2* (OR = 2.59) P21 (RAC1) activated kinase 2 The p21 activated kinases (PAK) are critical effectors that link Rho GTPases to cytoskeleton reorganization and nuclear signaling. The PAK proteins are a family of serine/threonine kinases that serve as targets for the small GTP binding proteins, CDC42 and RAC1, and have been implicated in a wide range of biological activities. The protein encoded by this gene is activated by proteolytic cleavage during caspase-mediated apoptosis, and may play a role in regulating the apoptotic events in the dying cell.
SLC16A6* (OR = 0.32) Solute carrier family 16 member 6 Predicted to enable monocarboxylic acid transmembrane transporter activity. Predicted to be located in and is an integral component of plasma membrane.
ZC3H3* (OR = 0.19) Zinc finger CCCH-type containing 3 Predicted to enable SMAD binding activity. Involved in regulation of mRNA polyadenylation. Located in nucleus.
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Platinum‑based chemotherapy GWAS

A secondary GWAS of patients who received platinum-based chemotherapy did not identify any SNPs that reached genome-wide significance. Twenty-seven SNPs were suggestive of genome-wide significance (Table 2). Of these, the minor allele of 6 SNPs were associated with development of CIPN (OR > 1.0), while the minor allele of 21 variant SNPs were associated with lower odds of developing CIPN (OR < 1.0, 95% CI < 1.0, Table 2). Using genetic information from EVEP and NCBI, five genes were found to contain these SNPs (Tables 2 and 3) [25, 26]. Two genes contained SNPs that all had OR > 1 (95% CI > 1.0), indicating the presence of a minor allele was associated with developing CIPN. Three genes contained SNPs that all had OR < 1 (95% CI < 1.0), indicating the presence of a minor allele was associated with a lower risk of developing CIPN (Tables 2 and 3).

Taxane and vinca alkaloid‑based chemotherapy GWAS

Two additional GWAS were completed analyzing patients who received taxane and vinca alkaloid-based chemotherapy. Neither identified any SNPs that reached genome-wide significance or was suggestive of genome-wide significance.

Candidate gene analysis

No SNPs within 50 kb pairs of the 33 genes previously associated with CIPN from the MASCC Neurological Complications Working Group Overview of 2019 and similar studies achieved genome-wide significant or suggestive of genome-wide significance. Table 4 displays two SNPs with the lowest p-values within 50 kb from each gene.

Table 4:

SNPs within 50 kb of candidate genes from 2019 MASCC Neurological Complications Working Group Overview. No SNPs were suggestive of genome wide significance (p-value all greater than <1x10–5), therefore this table is only displaying two SNPs within 50 kb from each gene (lowest two p-values).

CHROMOSOME GENE POSITION ALLELE 0 ALLELE 1 ALLELE 1 FREQUENCY BETA ODDS RATIO HIGHER 95% CI LOWER 95% CI P-VALUE GENE WITHIN 50 KB OF SNP
18 63919403 A C 23% −1.05E-05 1.00 1.29 0.77 2.78E-05 SERPINB2
16 82622189 C T 18% −1.35E-05 1.00 1.31 0.76 3.41E-05 CDH13
4 65396784 A G 25% 2.14E-05 1.00 1.28 0.78 5.93E-05 EPHA5
16 83513791 C T 5% 4.39E-05 1.00 1.63 0.61 6.08E-05 CDH13
8 1919487 T C 6% −8.24E-05 1.00 1.59 0.63 1.21E-04 ARHGEF10
18 53317052 T C 10% −7.17E-05 1.00 1.42 0.70 1.39E-04 DCC
18 53322836 A C 10% −7.17E-05 1.00 1.42 0.70 1.39E-04 DCC
13 95295322 C T 9% −1.05E-04 1.00 1.49 0.67 1.79E-04 ABCC4
2 203897604 G T 21% 8.54E-05 1.00 1.30 0.77 2.20E-04 CTLA4
19 45401800 CA C 24% −8.55E-05 1.00 1.28 0.78 2.35E-04 ERCC1
19 45401800 CA C 24% −8.55E-05 1.00 1.28 0.78 2.35E-04 ERCC2
8 1816739 C A 47% −8.45E-05 1.00 1.23 0.81 2.77E-04 ARHGEF10
4 182810730 A T 16% 1.27E-04 1.00 1.33 0.75 2.99E-04 TENM3
13 95075607 G A 14% −1.59E-04 1.00 1.37 0.73 3.45E-04 ABCC4
4 182348375 C T 5% 2.57E-04 1.00 1.61 0.62 3.69E-04 TENM3
19 43545729 G T 5% 2.67E-04 1.00 1.64 0.61 3.69E-04 XRCC1
1 151835038 G A 17% 1.63E-04 1.00 1.33 0.75 3.87E-04 THEM5
1 151831288 C G 14% −1.96E-04 1.00 1.38 0.72 4.12E-04 THEM5
6 3157554 C T 5% 3.10E-04 1.00 1.62 0.62 4.36E-04 TUBB2A
7 87467135 GTGCTGT G 3% 4.09E-04 1.00 1.80 0.56 4.73E-04 ABCB1
9 104789771 C CCACT 12% 2.48E-04 1.00 1.40 0.72 5.07E-04 ABCA1
12 32451710 C T 16% −2.17E-04 1.00 1.34 0.75 5.09E-04 FGD4
2 221583972 T G 43% 2.03E-04 1.00 1.24 0.81 6.39E-04 EPHA4
7 87568035 G A 38% −2.00E-04 1.00 1.23 0.81 6.53E-04 ABCB1
4 65330904 C A 36% −2.99E-04 1.00 1.26 0.80 8.92E-04 EPHA5
16 70697967 C T 3% −8.58E-04 1.00 1.81 0.55 9.80E-04 VAC14
19 1213879 C T 6% 7.17E-04 1.00 1.60 0.63 1.04E-03 MIDN
12 32538144 T C 30% 3.95E-04 1.00 1.26 0.79 1.16E-03 FGD4
3 96894070 G C 6% 7.72E-04 1.00 1.57 0.64 1.16E-03 EPHA6
3 97100763 A G 19% 4.94E-04 1.00 1.32 0.76 1.23E-03 EPHA6
2 221505338 A T 48% −4.36E-04 1.00 1.24 0.80 1.36E-03 EPHA4
6 170506340 C T 4% 1.09E-03 1.00 1.71 0.59 1.39E-03 PSMB1
15 34261956 G A 34% 4.82E-04 1.00 1.26 0.79 1.40E-03 SLC12A6
19 10297763 A C 7% 8.95E-04 1.00 1.52 0.66 1.45E-03 ICAM1
20 38086209 G C 6% −1.11E-03 1.00 1.62 0.62 1.57E-03 RPRD1B
9 104916516 C T 27% −5.97E-04 1.00 1.28 0.78 1.64E-03 ABCA1
16 70694074 G C 43% −5.34E-04 1.00 1.24 0.81 1.68E-03 VAC14
10 95100709 T G 48% 6.32E-04 1.00 1.24 0.81 2.02E-03 CYP2C8
19 45354988 G A 6% −1.60E-03 1.00 1.67 0.60 2.12E-03 ERCC2
19 45364748 T A 44% 6.76E-04 1.00 1.24 0.81 2.13E-03 ERCC1
20 38059968 C G 19% −9.29E-04 1.00 1.32 0.76 2.29E-03 RPRD1B
2 203894729 A G 16% −1.40E-03 1.00 1.34 0.74 3.22E-03 CTLA4
19 10323992 T C 15% 1.51E-03 1.00 1.35 0.74 3.48E-03 ICAM1
6 170583923 T C 4% −2.75E-03 1.00 1.68 0.59 3.62E-03 PSMB1
10 95004848 A G 3% 3.22E-03 1.00 1.84 0.55 3.62E-03 CYP2C8
15 34285822 T C 27% 1.29E-03 1.00 1.28 0.79 3.62E-03 SLC12A6
6 3138184 A AT 35% 1.30E-03 1.00 1.27 0.79 3.76E-03 TUBB2A
18 63908773 A G 23% −1.51E-03 1.00 1.28 0.78 4.09E-03 SERPINB2
21 43028665 G A 39% −1.40E-03 1.00 1.24 0.80 4.36E-03 PKNOX1
1 109677464 C G 45% 1.58E-03 1.00 1.23 0.82 5.30E-03 GTSM1
19 43533218 C G 17% −2.37E-03 1.00 1.33 0.75 5.69E-03 XRCC1
21 42978791 GT G 5% 4.47E-03 1.00 1.68 0.60 5.94E-03 PKNOX1
11 67623375 A G 13% −2.74E-03 1.00 1.36 0.73 5.99E-03 GSTP1
11 67623890 A C 13% −2.74E-03 1.00 1.36 0.73 5.99E-03 GSTP1
19 1254123 G A 41% −2.03E-03 1.00 1.24 0.80 6.42E-03 MIDN
6 35412221 G A 13% −3.82E-03 1.00 1.38 0.72 8.08E-03 PPARD
1 109665467 A T 37% −2.52E-03 1.00 1.23 0.81 8.34E-03 GTSM1
1 52591811 G A 27% −3.38E-03 1.00 1.27 0.78 9.62E-03 GPX7
6 35311019 C A 20% 4.24E-03 1.00 1.31 0.77 1.09E-02 PPARD
5 664090 C CG 12% 5.58E-03 1.01 1.41 0.72 1.15E-02 CEP72
1 52630054 T C 10% 6.19E-03 1.01 1.45 0.70 1.17E-02 GPX7
7 99609320 A C 6% 8.49E-03 1.01 1.62 0.63 1.23E-02 CYP3A5
5 87437561 A G 3% 1.18E-02 1.01 1.89 0.54 1.31E-02 CCNH
5 669327 G A 3% −1.23E-02 0.99 1.87 0.52 1.32E-02 CEP72
7 99642556 A G 10% 9.04E-03 1.01 1.48 0.69 1.64E-02 CYP3A5
5 87375153 T C 47% −1.16E-02 0.99 1.23 0.79 3.70E-02 CCNH
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Discussion

Using a novel EHR-derived definition of CIPN, this GWAS compared patients who met CIPN criteria against unaffected patients and identified 60 SNPs within 11 genes that may be involved in the development of CIPN. This HER-derived, real-world definition allowed for identification of 528 patients (57%) who developed CIPN after receiving neurotoxic chemotherapy.

Sixty SNPs fell within genes with known functions that may be important in the regulation of cellular damage and the development of CIPN, particularly those that encode plasma membrane proteins (Table 3). In the total population, SNPs suggestive of lower odds of developing CIPN (OR < 1.0, 95% CI < 1.0) fell within the following genes: RCOR1, which encodes a protein involved with neural cell differentiation; CLDN14, which encodes an integral membrane protein that creates a barrier for water and solute entry into the cell; TRIM56, which is involved in the defense response to other organisms and regulation of macromolecule metabolic processes; and ADGRD1, a transmembrane protein that transduces extracellular signals [25, 26]. All SNPs that suggested association with development of CIPN (OR > 1.0, 95% CI > 1.0) fell within three genes, including TMC2, which is seen in hereditary disorders of balance, and TGFBR3, a membrane proteoglycan that has been associated with various cancers when expression is reduced [25, 26].

In the GWAS of patients who received platinum-based chemotherapy, SNPs implicated with CIPN fell within genes of similar function (Table 3). PAK2 encodes kinases important to cytoskeleton reorganization and nuclear signaling and play a role in regulating apoptosis, and SLC16A6 encodes a protein that is an integral component of the plasma membrane [25, 26].

These genes collectively intimate that both neuronal development (RCOR1, TMC2) and cellular permeability to neurotoxic chemotherapy (CLDN14, ADGRD1, SLC16A6) may play important roles in the development of CIPN. However, the presence of a suggestive SNP within the coding region of a gene does not necessarily entail a change in the function or abundance of the gene product, and further work is needed to investigate the biological functions as it relates to CIPN.

Previous studies have identified other SNPs and genes associated with CIPN, often done prospectively in a clinical setting [3, 6, 8, 10–12, 27]. The MASCC Neurological Complications Working Group Overview from 2019 identified multiple genes from previous studies that were associated with CIPN. In our analysis, none of these genes contained SNPs of genome-wide significance or suggestive of genome-wide significance. Variations in methodology, such as including multiple chemotherapy agents compared to single agents, and variations between populations, may have led to the differences observed between this GWAS and previous studies.

Another important study evaluated ICD codes and neuropathic pain medications as a proxy for CIPN, similar to this analysis, which helps provide context to imperfect EHR-derived data [28]. These researchers found both diagnosis codes (broad and narrow codes), and neuropathic pain medication prescription (gabapentin, pregabalin, and duloxetine) to underestimate incidence of CIPN compared to observed rates in a previous metanalysis (18.1% highest incidence compared to 58–78%) [28, 29]. While similar methods, our analysis used a wider range of ICD codes (Appendix Table 1) and included additional neuropathic pain medications (venlafaxine, amitriptyline, nortriptyline). Observed incidence in this study was comparable to previously observed rates (57% versus 58–78%) [29].

The limitations of this study include a single regional health system experience using an EHR-derived definition of CIPN. The most common race in our population was White or Caucasian (89.8%), which is higher than the state population (70.7%) [30]. Although race is an imperfect proxy for genetic ancestry, it is imperative to increase racial diversity in future studies [4, 31]. Our total sample included patients who had received various chemotherapies, which may confound results if genetic predisposition to CIPN differ based on individual medication’s mechanism of action or class effects. We accounted for this by completing a separate GWAS for the most common chemotherapy classes, only finding SNPs suggestive of genome-wide significance in the platinum group.

The EHR-derived definition differs from previous studies that have historically used patient reported outcomes to diagnose CIPN, such as the National Cancer Institute Common Terminology Criteria for Adverse Events (NCI-CTCAE) and the Total Neuropathy Score, and with previous EHR-related claims data [8, 29, 32]. Additionally, our definition did not capture patients who had dose reductions of chemotherapy related to CIPN or those who had significant CIPN but were not prescribed a neuropathic pain medication or had a diagnosis code charted. Our statistical analysis did not account for cumulative dosing or previous therapies received, given the limitations of imperfect EHR data.

This pharmacogenomic study of patients who received chemotherapy known to cause neuropathy identified multiple genetic loci that may be candidates for further validation. This unique EHR-derived definition, as utilized here, may allow for multi-institution collaboration and could increase sample sizes and population diversity in the future. Genetic analyses of CIPN following less frequently used medications (i.e., eribulin, enfortumab vedotin) may also be possible using this definition. Further research should compare this EHR-derived definition to patient reported outcomes to verify accuracy, particularly given the lack of validation of the genes from the MASCC Overview in our results. Lastly, with larger sample sizes and more studies in this area, researchers should develop risk prediction models to estimate the likelihood of developing CIPN. This would allow for a personalized approach to treatment regimens and reduce treatment related adverse events in newly identified high-risk patients.

Supplementary Material

Appendix

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s00520-025-09392-y.

Acknowledgements

The authors would like to thank Kiley Vander Wyst, PhD, of the Clinical Research Support Team, within the Office of the Vice Chancellor of research at the University of Colorado Anschutz Medical Campus, for regulatory assistance, as well as Health Data Compass, part of the Research Informatics Office at the University of Colorado Anschutz Medical Campus, particularly Kelli Hodge and Becky Bui, for EHR data collection.

Funding

University of Colorado Cancer Center Support Grant P30CA04934.

Footnotes

Declarations

Ethics approval This project was approved by the Colorado Multiple Institutional Review Board, PAM001–1. Actions by COMIRB [are] guided by the principles of respect for persons, beneficence, and justice set forth in the Ethical Principles and Guidelines for the Protection of Human Subjects of Research (often referred to as the Belmont Report).

Competing interests The authors have no relevant financial or nonfinancial interests to disclose.

Data availability

No datasets were generated or analysed during the current study.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix
NIHMS2195451-supplement-Appendix.xlsx (12.6KB, xlsx)

Data Availability Statement

No datasets were generated or analysed during the current study.

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