Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 May 22.
Published in final edited form as: J Gastroenterol. 2020 Jul 17;55(10):1000–1009. doi: 10.1007/s00535-020-01703-w

Constant-Severe Pain in Chronic Pancreatitis is Associated with Genetic Loci for Major Depression in the NAPS2 Cohort

Ellyn Dunbar 1,2, Phil J Greer 1, Nadine Melhem 3, Samer Alkaade 4,a, Stephen T Amann 5, Randall Brand 1, Gregory A Coté 6,b, Christopher E Forsmark 7, Timothy B Gardner 8, Andres Gelrud 1,9,c, Nalini M Guda 10, Jessica LaRusch 1,d, Michele D Lewis 11, Jorge D Machicado 1,e, Thiruvengadam Muniraj 1,f, Georgios I Papachristou 1,g, Joseph Romagnuolo 12,h, Bimaljit S Sandhu 13,i, Stuart Sherman 6, Charles M Wilcox 14, Vikesh K Singh 15, Dhiraj Yadav 1, David C Whitcomb 1,2,16, NAPS2 study group
PMCID: PMC9124361  NIHMSID: NIHMS1803073  PMID: 32681239

Abstract

Background:

Pain is the most debilitating symptom of recurrent acute pancreatitis (RAP) and chronic pancreatitis (CP) and often requires chronic opioids or total pancreatectomy with islet autotransplantation to manage. Pain is a complex experience that can be exacerbated by depression and vice versa. Our Aim was to test the hypothesis that depression-associated genes are associated with a constant-severe pain experience in RAP/CP patients.

Study:

A retrospective study was done using North American Pancreatitis Study II (NAPS2) genotyped RAP and CP patients with completed case report forms (n=1,357). Subjects were divided based on pattern of pain and pain severity as constant-severe pain (n=787) versus not constant-severe pain (n=570) to conduct a nested genome wide association study. The association between reported antidepressant medication use and depression gene loci was tested.

Results:

Constant-severe pain was reported in 58% (n=787) of pancreatitis patients. No differences in sex or alcohol consumption were found based on pain severity. Antidepressant use was reported in 28% (n=223), and they had lower SF-12 mental quality of life (MCS, p < 2.2×10−16). Fifteen loci associated with constant-severe pain (p<0.00001) were found to be in or near depression-associated genes including: ROBO2, CTNND2, SGCZ, CNTN5 and BAIAP2. Three of these genes respond to antidepressant use (SGCZ, ROBO2, and CTNND2).

Conclusions:

Depression is a major co-factor in the pain experience. This genetic predisposition to depression may have utility in counseling patients and in instituting early antidepressant therapy for pain management of pancreatitis patients. Prospective randomized trials are warranted.

Keywords: pain chronic, chronic pancreatitis, depression, antidepressants, Human Genetics

Introduction

Chronic pancreatitis (CP) is a syndrome of inflammatory destruction of the pancreas ending in irreversible damage with variable degrees of exocrine pancreatic insufficiency (EPI), diabetes mellitus (DM) and constant-severe pain.[1–3] Progression to CP typically begins with acute pancreatitis (AP) and recurrent AP (RAP), but even at these earlier stages, there are negative effects on physical and mental health and quality of life (QOL). [4–6] The etiology of AP, RAP and CP is complex and associated with toxic and metabolic factors such as alcohol, smoking, hypercalcemia, hypertriglyceridemia, genetic factors such as DNA sequence variants in or near CASR, CEL, CFTR, CLDN2, CPA1, CTRC, PRSS1, SPINK1, TRPV6, UBR1 and others, and obstructive etiologies. [7–9] Additional genetic variants and environmental factors predispose to secondary complications such as diabetes [10–12] and pancreatic cancer.[13–17] The major disabling feature that drives low quality of life is severe, constant pain, a condition that develops in 1 in 3 CP patients.[1, 5, 6] The reason for variability of this feature among pancreatitis patients is unknown, but may include genetic factors.

Pain is a subjective experience that encompasses the generation of pain signals from the injured organ, the physiological and pathological reflex responses, and higher brain responses linked to regions associated with emotion and motivation (prefrontal region, limbic system, and midbrain periaqueductal gray) to the pain signals.[18] Depression is recognized as a comorbid diagnosis in a variety of pain disorders and antidepressants have been empirically used in patients with CP to manage pain.[19] However, the effects of depression on the pain experience may be overlooked, and it is unclear as to who is likely to respond to antidepressant medications or other therapies in the management of the constant-severe pain experience in CP and the mechanisms implicated in treatment response.

Major Depressive disorder (e.g. ICD-10 F33.2) is characterized by recurrent episodes of depression lasting at least two weeks and can include lowered energy and enjoyment of activities, depressed mood, different patterns of sleeping and eating, anxiety, lack of focus, guilt, and medically unexplainable symptoms.[20] Depression can be influenced by environmental factors—such as illness, financial instability, and childhood trauma—and genetic factors across many loci.[21, 22] The heritability of depression has been estimated to be between 30% and 40% based on twin studies.[21, 23] Individuals of both sexes with depression are also at an increased risk for certain physical disorders such as diabetes mellitus, stroke, and heart disease.[21, 24] Patients with depression tend to have higher inflammatory immune responses; similarly, cytokines can induce depression and depression-like symptoms in patients.[25] Therefore, it is possible that some RAP/CP patients that are genetically prone to depression are also susceptible to altered inflammation and more severe pain.

We conducted an exploratory study in a well phenotyped and genotyped cohort of patients with RAP and CP to determine whether genetic loci that have previously been demonstrated to be associated with depression were overrepresented in the pancreatitis patients who also reported the most constant-severe pain. Our findings of associations between the constant-severe pain experience and several depression risk loci that are known to be responsive to antidepressant medications, and may respond to other therapies, establish this approach as a pathway toward more effective, personalized treatment of the most disabling complication of pancreatitis.

Materials and Methods

Study Population

CP and RAP patients and controls were ascertained from the North American Pancreatitis II (NAPS2) studies (NCT01545167).[1, 6, 26–29] NAPS2 was launched in 1999 to determine the contribution of known risk factors (alcoholism and smoking) to CP and to discover new genetic risk factors.[26, 28, 29] The concept was to prospectively ascertain 1000 subjects with RAP and CP and spouse-friend controls with detailed demographic information and family history to define and quantify pancreatic disease-associated risk factors and exposures (based on TIGAR-O [30]), disease onset and progression to test the Sentinel Acute Pancreatitis Event (SAPE) hypothesis, [31, 32] and the prevalence and timing of secondary complications including pain, exocrine pancreatic insufficiency (EPI), diabetes (before or after AP), quality of life, etc. Biomarker results from the medical records were recorded to determine disease features and stages (e.g. pancreas imaging, list of secondary diagnoses, special tests, etc) and blood was collected to measure serum biomarkers and DNA for genetic variants).

NAPS2 occurred in three phases, the original NAPS2 cohort (2000-2006) designed to ascertain 1000 RAP/CP patients, the NAPS2-continuation and validation study (NAPS2-CV) (2008-2012) designed to ascertain an additional 500 CP patients for GWAS studies, and NAPS2-ancillary study (NAPS2-AS) designed to ascertain 250 CP patients and 250 controls of African ancestry). Between sub-studies minor changes were made to the case report forms to clarify ambiguities or uncertainties in previous versions (e.g. the physician was asked whether the patient was on pancreatic enzyme replacement therapy, but initially they were not asked if it was for EPI or pain). The result was over 50 direct and secondary publications including defining the role of alcohol and smoking in CP, [27, 33, 34] pain patterns and their effect on quality of life,[6, 35, 36] differences among patients based on age,[6, 35, 36] sex[37] and ancestry, [11, 28, 38] and multiple genetic findings including the first CP genome wide association study (GWAS) identifying PRSS1-2 and CLDN1 risk loci,[2] a new cystic fibrosis related syndrome,[39] complex genetic risks, [38–41] establishing the foundation for a new mechanistic definition of CP[3] and providing the rationale for precision medicine for pancreatic diseases.[42–44]

The final subset of the NAPS2 cohort used in this study included RAP and CP subjects (n=1,357). The diagnosis of RAP was based on two or more documented episodes of acute pancreatitis. CP was diagnosed based on validated imaging studies or histology.[26, 36] The study was constructed as a cross-sectional study including questionnaires described later. Only patients of European ancestry (EA) were included in the analysis to reduce heterogeneity since the majority of subjects recruited for NAPS2 were of EA. Previous genotyping was done on the Illumina HumanOmniExpress BeadChip.[2] Genotype data was prepared for imputation using the McCarthy Group pre-imputation checking tools and imputed against the 1000 genomes phase-3 reference panel on the Sanger imputation server using EAGLE2 for pre-phasing and PBWT for imputation.[45–47] Resultant imputed files were filtered based on the INFO score ≥0.5, renamed based on position, filtered for biallelic positions only, and filtered for genotype completeness at 90% leaving a total of 9,251,575 SNPs with a MAF >0.01 for our analysis.

Questionnaires

Two sets of questionnaires were used to collect detailed information; one administered to patients by a trained research coordinator and the other completed by the enrolling physician. The patient questionnaires collected information on demographics (including current and maximal weight and height to calculate body mass index (BMI)), diabetes, EPI, personal and family history, exposure to alcohol and tobacco, medication use, mental and physical quality of life using Short Form-12 (SF-12), pain experience using a visual analogue scale, pain frequency and severity, and McGill pain score.[1, 6]. The questionnaires in NAPS2 original and NAPS2-CV were identical in the core elements, but additional questions on the use of specific medication for pancreatic disease (rather than a list of all medicines) and their perceived utility were used in NAPS2-CV and NAPS2-AS so that not all information was available in all patients, resulting in missing information on antidepressants from those individuals (n=547).

The enrolling physician provided information on age at onset and diagnosis of CP, exocrine and endocrine insufficiency, disease etiology, TIGAR-O risk factors, imaging findings, treatments tried and their perceived effectiveness.[48] The detailed assessment of alcohol and smoking in the NAPS2 cohort has been previously reported.[26] “Never drank” is less than 20 drinks in a lifetime. Smoking history was obtained from the patients’ case report forms (CRF) with “never smoked” being less than 100 cigarettes in a lifetime.

Pain, Depressive Symptoms, and Antidepressant Use

Patterns of pain were defined following Mullady[1] using a 6-category severity-frequency classification system with O = no pain; A = episodes of mild pain; B = constant mild to moderate pain; C = episodes of severe pain; D = constant mild and episodes of severe pain; E = constant-severe pain.[1] For this study, subjects responding with D or E were classified as constant-severe pain, while subjects responding with O, A, B, or C were classified as not constant-severe pain. This combination of constant and severe pain had the highest impact on QOL.

Depression was not directly measured by the SF-12; however, a self-reported symptom of depression and a mental component summary (MCS) was gathered and reported as proxies in this study. The depressive symptom (“Felt Blue”) was assessed using the SF-12 question “Have you felt downhearted and blue?” with reference to the previous 4 weeks and rated on a Likert scale of 1 “All of the time” to 6 “None of the time.” The “Felt Blue” variable was a dichotomized version of the Likert responses with responses 1, 2, or 3 corresponding to “Yes” and 4, 5, or 6 corresponding to “No.” The MCS was used as a measure of mental QOL, with a higher score indicating a greater QOL. [35] The MCS has been used previously as a measure of mental health and depressive disorders. [49, 50]

Antidepressant use was reported in free-text format in the patient and/or physician case report forms. Text mining procedures in R were used to extract the antidepressants.[51] A list of the queried drugs, both brand name and corresponding generic names, can be found in Supplemental Table 1. The antidepressant variable was binary, with 1 meaning antidepressants were reported in the CRF and not used as pain medication and 0 meaning no antidepressants were reported. The majority of CP and RAP patients from the original NAPS2 cohort that were taking antidepressants were taking selective serotonin reuptake inhibitors (SSRIs, 56%), followed by tricyclic antidepressants (TCAs, 19%), serotonin and norepinephrine reuptake inhibitors (SNRIs, 16%), and norepinephrine-dopamine reuptake inhibitor (NDRIs, 10%) (Supplemental Table 1).

Genetic Data Analysis

The genetic analysis was constructed as a candidate gene review within a nested genome wide association study (GWAS) data set of subjects with RAP/CP subjects based on pain patterns. The RAP and CP patients were combined, then classified as one of two groups: constant-severe pain (cases) or not constant-severe pain (controls). The nested GWAS was conducted using PLINK 1.9 software.[52] Quality control methods have been previously reported.[2] Data was fit to a logistic regression to test for associations. To control for ancestry, the first 4 principle components of ancestry were included as covariates. The minor allele frequency (MAF) was set to 0.01. Single nucleotide polymorphisms (SNPs) with a p-value of less than 1×10−4 were chosen to continue in the analysis.

SNPs meeting the required significance threshold were then clumped into groups based on linkage disequilibrium (LD) (± 250 kb from index SNP, r2 > 0.5) using the “clump” command in PLINK.[52] The lead SNPs (p-value ≤ 0.0001) for each clump were annotated with gene names based on build GRCh37/hg19. These genes were then compared to a list of genes associated with unipolar depression and antidepressant response obtained from the GWAS Catalog in October 2019.[53] Odds ratios (OR) for the lead pain SNPs stratified by the binary antidepressant usage variable were calculated with Cochran-Mantel-Haenszel (CMH) statistics using the “within” and “mh” commands in PLINK.[52]

Demographic data was compiled and analyzed using R version 3.6.0. Univariant comparisons were performed based on the demographic variables using Pearson chi-squared test for categorical data. Two-tailed p-values <0.05 were considered statistically significant (Table 1).[51] Zoom plots were created using the online platform LocusZoom, and exported using Gapplin (Supplemental Figures 1–5).[54, 55]

Table 1. Association of demographic and depression phenotypes with constant-severe pain.

Percentages shown next to the counts are column percentages within each variable.

Variable Level Not Constant-severe Pain (n=570) Constant-severe Pain (n=787) Total (n=1357) p-value
Age 1 Mean (sd) 51.7 (16.3) 46.5 (15.4) 48.7 (16.0) ***
Sex Male 281 (49.3%) 407 (51.7%) 688 (50.7%)
Female 289 (50.7%) 380 (48.3%) 669 (49.3%)
Alcohol Never 118 (20.9%) 171 (21.8%) 289 (21.4%)
Ever 447 (79.1%) 615 (78.2%) 1062 (78.6%)
Missing 5 1 6
Smoking Never 220 (38.8%) 237 (30.3%) 457 (33.9%)
Ever 347 (61.2%) 546 (69.7%) 893 (66.1%) **
Missing 3 4 7
Antidepressant Use No 300 (75.2%) 287 (69.8%) 587 (72.5%)
Yes 99 (24.8%) 124 (30.2%) 223 (27.5%)
Missing 171 376 547
“Felt Blue” No 281 (86.5%) 312 (76.3%) 593 (80.8%)
Yes 44 (13.5%) 97 (23.7%) 141 (19.2%) ***
Missing 245 378 623
EPI No 335 (71.9%) 501 (69.6%) 836 (70.5%)
Yes 131 (28.1%) 219 (30.4%) 350 (29.5%)
Missing 104 67 171
Diabetes No 354 (72.7%) 568 (74.6%) 922 (73.9%)
Yes 133 (27.3%) 193 (25.4%) 326 (26.1%)
Missing 83 26 109
Mental QOL Mean (sd) 46.8 (11) 41.8 (12) 43.7 (11.9) ***
Missing 96 35 131
Open in a new tab

Stars indicate level of significance within each variable and with pain severity

*

p<0.05,

**

p<0.01,

***

p<0.001.

Footnote: 1. Age of ascertainment.

Results

Patient characteristics

The characteristics of the RAP and CP subjects classified as constant-severe pain or not constant-severe pain and the associations between constant-severe pain and general risk factors or depression-associated features are summarized in Table 1. Age, smoking, “Felt Blue”, and MCS are all associated with constant-severe pain. Antidepressant usage was associated with lower MCS (Wilcoxon rank sum test with continuity correction, W=208590, p < 2.2x10−16).

Genetic associations between constant-severe pain and depression genes.

There were a total of 1,357 genotyped individuals of European ancestry with pancreatitis and core pain/depression information in the dataset. Candidate chromosomal loci for depression-associated genes in patients with a constant-severe pain phenotype were identified using PLINK by comparing not constant-severe pain with constant-severe pain. Candidate loci were identified by lead SNPs (p < 0.0001), clumped with other SNPs within 250 kb and with r2 greater than 0.5 with the lead SNP.[52] Genes associated with the lead SNPs of the clumps were compared to genes associated with depression and reported in the GWAS Catalog identifying 15 pain loci containing depression genes.[53] The SNP most significantly associated with pain and with a depression-associated gene was rs12449867 on chromosome 17 near BAIAP2-AS1 (OR 1.44, p=2.0x10−5 for pain) (Table 2). Additionally, three genes (ROBO2, CTNND2, and SGCZ (Table 2)) were also reported in the GWAS Catalog as being associated with antidepressant response.[53] Individual zoom plots of the leading loci are in Supplemental Figures 1–5. The LD regions shown in the zoom plots were based on EA.

Table 2. GWAS results for 15 depression SNPs associated with pain in the NAPS2 data.

Chromosomal locations are based on build GRCh37/hg19.

Chr Location (bp) SNP P A1/A21 OR (A1) 95% CI Freq. A1 Gene
2 15,686,142 rs141909432 4.8x10−5 A/G 3.97 2.04,7.71 0.02 NBAS
2 55,331,982 rs2968817 7.6x10−5 A/G 0.69 0.57,0.83 0.29 RTN4
3 12,816,143 rs113388258 2.4x10−5 C/T 2.03 1.46,2.82 0.06 CAND2, TMEM40
3 77,151,787 rs4624600 5.5x10−5 C/T 1.36 1.17,1.59 0.35 ROBO2*
5 11,187,984 rs59442633 2.9x10−5 C/T 1.81 1.37,2.38 0.08 CTNND2*
5 146,034,762 rs458909 9.4x10−5 A/C 3.44 1.85,6.39 0.02 PPP2R2B
8 14,471,243 rs11300774 6.1x10−5 T/TA 0.68 0.56,0.82 0.25 SGCZ*
11 100,059,361 rs2123323 7.0x10−5 T/C 1.39 1.18,1.64 0.46 CNTN5
11 100,126,103 rs36106152 7.9x10−5 G/GA 0.71 0.59,0.84 0.33 CNTN5
12 118,024,434 rs71450224 5.1x10−5 A/AAAAG 0.68 0.56,0.82 0.26 KSR2
17 79,004,271 rs12449867 2.0x10−5 C/T 1.44 1.22,1.71 0.34 BAIAP2-AS1
17 79,031,825 rs9898347 9.6x10−5 A/G 0.71 0.60,0.84 0.35 BAIAP2
17 79,036,107 rs34176221 5.9x10−5 AT/A 1.39 1.19,1.64 0.45 BAIAP2
18 49,961,950 rs1619323 4.2x10−5 C/T 0.66 0.54,0.81 0.22 DCC
22 45,353,108 rs8137390 4.3x10−5 G/A 1.50 1.24,1.82 0.20 PHF21B
Open in a new tab
*

Indicates regions associated with antidepressant response.

Footnote 1: A1 is the minor allele, A2 is the major allele.

The use of antidepressants in patients with pain was assessed using Cochran-Mantel-Haenszel analysis. The result for each SNP associated with constant-severe pain was correlated with antidepressant usage (Table 3). The most significantly associated locus after stratification by antidepressant use is at Chromosome 8:14,471,243, rs11300774 (OR 0.636, p=4.38x10−6). Genotype counts for each SNP in cases and controls are reported in Table 4.

Table 3.

CMH results for lead SNPs when genotype and pain are grouped by antidepressant use.

Chr SNP A1 MAF A2 CHISQ P OR SE L95 U95
2 rs141909432 A 0.016 G 15.16 9.89x10−5 3.221 0.327 1.698 6.113
2 rs2968817 A 0.291 G 16.32 5.36x10−5 0.691 0.092 0.578 0.828
3 rs113388258 C 0.059 T 18.73 1.51x10−5 2.077 0.17 1.489 2.898
3 rs4624600 C 0.347 T 18.13 2.06x10−5 1.435 0.085 1.215 1.695
5 rs59442633 C 0.082 T 18.43 1.76x10−5 1.84 0.144 1.388 2.439
5 rs458909 A 0.017 C 17.48 2.90x10−5 3.581 0.323 1.9 6.748
8 rs11300774 T 0.246 TA 21.09 4.38x10−6 0.636 0.099 0.524 0.771
11 rs2123323 T 0.461 C 11.96 5.44x10−4 1.326 0.082 1.13 1.555
11 rs36106152 G 0.329 GA 16.44 5.03x10−5 0.699 0.089 0.588 0.831
12 rs71450224 A 0.262 AAAAG 16.62 4.56x10−5 0.677 0.096 0.561 0.817
17 rs12449867 C 0.336 T 16.68 4.43x10−5 1.415 0.085 1.197 1.672
17 rs9898347 A 0.355 G 12.4 4.30x10−4 0.737 0.087 0.622 0.874
17 rs34176221 AT 0.445 A 11.19 8.23x10−4 1.315 0.082 1.12 1.543
18 rs1619323 C 0.217 T 17.35 3.10x10−5 0.653 0.103 0.534 0.799
22 rs8137390 G 0.202 A 15.99 6.37x10−5 1.485 0.099 1.223 1.804
Open in a new tab

Table 4. Genotypic distribution among cases and controls.

Counts represent number of individuals.

Chr rsID Gene A1 (minor) A2 (major) Total Not Constant-severe Pain Constant-severe Pain
A1/A1 A1/A2 A2/A2 Control A1/A1 A1/A2 A2/A2 Cases
2 rs141909432 NBAS A G 1355 0 9 560 569 0 33 753 786
2 rs2968817 RTN4 A G 1356 47 274 248 569 59 303 425 787
3 rs113388258 CAND2,TMEM40 C T 1357 0 51 519 570 4 100 683 787
3 rs4624600 ROBO2 C T 1347 72 193 300 565 155 287 340 782
5 rs59442633 CTNND2 C T 1355 1 74 495 570 11 123 651 785
5 rs458909 PPP2R2B A C 1357 0 10 560 570 0 36 751 787
8 rs11300774 SGCZ T TA 1356 43 301 225 569 46 478 263 787
11 rs2123323 CNTN5 T C 1356 97 300 173 570 182 392 212 786
11 rs36106152 CNTN5 G GA 1357 65 231 274 570 82 381 324 787
12 rs71450224 KSR2 A AAAAG 1354 41 234 295 570 45 303 436 784
17 rs12449867 BAIAP2-AS1 C T 1355 49 239 281 569 99 376 311 786
17 rs9898347 BAIAP2 A G 1356 72 296 202 570 91 340 355 786
17 rs34176221 BAIAP2 AT A 1354 88 284 197 569 177 391 217 785
18 rs1619323 DCC C T 1355 31 195 343 569 36 260 490 786
22 rs8137390 PHF21B G A 1356 20 177 372 569 35 262 490 787
Open in a new tab

Discussion

Depression is a major, worldwide problem. It is estimated that at least 1 in every 6 individuals worldwide will experience depression during their lifetime, making depression the top cause of disability in the world.[23] Depression often starts during the teen years, persisting into adulthood. Like most psychiatric disorders, depression is a syndrome diagnosed using observation and self-report methods.[22]

Pain and depression are comorbid and reciprocal, with the severity of one increasing the severity of the other.[56, 57] Severe depression affects an estimated 85% of patients with chronic pain.[58] Chronic pain has a heritability of approximately 30%.[57] Patients with depression and a chronic pain disorder were less likely to recover from their pain, and future episodes of pain were predicted by the presence of severe depression. Patients with severe depression before surgery suffered more pain after surgery than patients without depression. Conversely, antidepressants may not be as effective at treating depression in patients with higher pain levels at baseline, with 94% of relapsing depression occurring in patients with mild to moderate pain. Fortunately, when treatment of depression is successful some symptoms of pain are also alleviated.[56]

Pain is the most important clinical feature associated with disability and poor mental and physical quality of life in patients with RAP and CP.[1, 6] The connection between pain in chronic pancreatitis and depression is known. For example, one study found that in patients with chronic pancreatitis, not caused by alcoholism, severe depression was associated with higher intensity of pain.[59] Additionally, depression was a predictor of hospital readmissions at 30 days in patients with chronic pancreatitis.[60] Pain is a predictor of relapsing depression, it is therefore reasonable to suggest that a longer duration of pancreatic pain would influence the severity of depression; although duration was not associated with the “Felt Blue” variable (Supplemental Table 2).[29] Thus, this is a major problem that must be addressed. Here we evaluated the possible role of underlying genetic risk of depression to the experience of constant-severe pain. Our approach was an exploratory study to determine whether depression-associated genes that were already discovered and well characterized were within regions associated with constant-severe pain in patients with RAP and CP.

Pain and depression genes in pancreatitis

Fifteen candidate loci with known depression-associated genetic risk variants that were associated with constant-severe pain phenotype loci (p<0.00001) were identified in our NAPS2 cohort. Additionally, the use of antidepressant medications indicates that over a quarter of patients were being treated with a trend toward higher use in constant-severe pain (30.2% constant-severe vs. 24.8% not constant-severe) but we could not determine if some patients initially had constant-severe pain that was improved with antidepressants and were therefore in the not constant-severe pain category at the time of ascertainment. We also saw an association with constant-severe pain and smoking (70% constant-severe vs. 61% not constant-severe, p<0.01); however, this result may be confounded by some subjects smoking to control pain.[34] Alcohol use was not significantly different between pain categories. However, patients in the constant-severe pain category had a lower MCS, indicative of a lower QOL associated with their pain. These data clearly indicate that depression is a major problem in patients with RAP and CP and that genetic loci with known depression-associated genetic risk variants are significantly associated with constant-severe pain.

Depression-associated genes

Multiple well-established depression-associated genes were associated with pain in pancreatitis patients including ROBO2, CTNND2, SGCZ, CNTN5, and BAIAP2. Three of these genes are also associated with response to antidepressants (ROBO2, CTNND2, SGCZ).[53] Further information on these genes can be found in the Supplemental Information. These findings may also provide mechanistic support to the empiric observation that some patients with CP respond to antidepressant medications. [19]

Clinical Implications

The identification of genetic risk variants for depression associated with the severe-constant pain phenotype may have important clinical implications. The data presented here is a retrospective, cross-sectional, observational cohort study that are not designed to study depression per se. Furthermore, genetic risks for complex conditions such as depression are not independently causal as multiple genetic, epigenetic, environmental, emotional and other contextual factors (e.g. childhood abuse) also contribute to the phenotype. Thus, further longitudinal studies that are designed to address issues of pain and depression in pancreatitis—including interventional studies—are still needed. Nevertheless, the associations identified here were strong, and some immediate applications should be considered.

Recognition by the physician that a patient with pancreatitis and pain has genetic risks for depression can be useful for providing patient education that they are more likely to have biology-based components to depression, that depression makes pain worse, and that addressing these symptoms may augment pain treatment. Furthermore, there may be benefit in early interventions such as cognitive behavioral therapy and, in some cases, detection of genetic risks in specific genes such as SGCZ, ROBO2, and CTNND2 may provide rationale for a trial of specific medications that are known to improve symptoms in patients with depression from other etiologies.

Limitations and future directions

This nested study has a small sample size, which reduces power to discover genetic variants associated with a phenotype using the accepted genome-wide significance threshold of 5x10−8.[61] Although no SNPs reached genome-wide significance as an independently associated factor, the study design was to identify previously validated depression genes within loci that were marginally associated with pain in RAP/CP. Thus, we do not believe that stringent thresholds for new genetic associations with correction for genome wide associations apply here. Since depression analysis was not a goal of the NAPS2 studies, the depression phenotype(s) were not well defined, and slight changes in the CRFs may have affected study precision and power (e.g. missing data). The text mining process used to identify antidepressants is limited by spelling errors present in the case report forms, recall bias, as well as the number of subjects that contained full pharmacologic data. However, the NAP2 phenotypes and CRFs were completed by expert clinicians so the accuracy of the overall data set is fundamentally superior to administrative data sets and most of the unclear text data was easily resolved. The temporal relationship between severe pain and use of antidepressants was also not ascertained. Thus, the relationships between pain, depression, and antidepressants could not be fully assessed in this study, but should be addressed in future studies.

Summary and conclusions

Pain is the most debilitating symptom of chronic pancreatitis and one of the most difficult to treat.[1, 62] Approximately 18% of patients with chronic pancreatitis also experience depression.[60] Pain can increase the severity of depression, and vice versa.[56] GWAS data has been used to study the comorbidity and overlapping risk alleles of depression in diseases like type 2 diabetes, metabolic syndrome, and inflammatory bowel disease, and now in pancreatitis.[23, 24, 63] Our findings suggest that there is an overlap of depression associated genes and constant-severe pancreatic pain.

Supplementary Material

Supplementary Information

Acknowledgements:

This research was partly supported by the NIDDK T32 DK063922-17 (DCW), NIH DK061451 (DCW), R21 DK098560 (DCW), U01 DK108306 (DCW, DY). This publication was also made possible in part by Grant Number UL1 RR024153 and UL1TR000005 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research (University of Pittsburgh. PI, Steven E Reis, MD). Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the NCRR or NIH.

The genotyping of the samples in this study were previously completed with the assistance of M. Michael Barmada PhD (deceased), additional phenotyped samples contributions by NAPS2 centers led by Michelle Anderson MD MS, Frank Burton MD (deceased), John Baillie MD MS (deceased), Peter Banks MD, Darwin Conwell MD, MS James DiSario MD, and Robert Hawes MD. Laboratory assistance of Kimberly Stello, Danielle Dwyer and staff of the Whitcomb Core laboratory was appreciated. Data collection was done with the assistance of the Epidemiology Data Center of the University of Pittsburgh (Stephen R. Wisniewski, PhD, director).

Abbreviations.

AP

Acute pancreatitis

BAIAP2-AS1

the BAIAP2 divergent transcript gene (or BAIAP2-DT)

BMI

body mass index

CMH

Cochran-Mantel-Haenszel statistic

CP

chronic pancreatitis

CRF

case report form

CTNND2

the catenin delta 2 gene (or GT24; NPRAP)

DM

diabetes mellitus

EPI

exocrine pancreatic insufficiency

EA

European ancestry

GWAS

genome wide association study

LD

linkage disequilibrium

MAF

minor allele frequency

MCS

mental component summary

NAPS2

North American Pancreatitis Study II

NDRI

antidepressant drug class of norepinephrine-dopamine reuptake inhibitors

OR

odds ratio

QOL

quality of life

RAP

recurrent acute pancreatitis

ROBO2

the roundabout guidance receptor 2 gene (or SAX3)

SGCZ

the sarcoglycan zeta gene (or ZSG1)

SF-12

Short form 12

SNP

Single nucleotide polymorphism

SSNRI

antidepressant drug class of serotonin and norepinephrine reuptake inhibitors

TIGAR-O

common risk and etiology list for pancreatitis including Toxic, Idiopathic, Genetic, Autoimmune, Recurrent Acute and Severe Acute pancreatitis, and Obstructive

Footnotes

Clinical Trials Registration: Clinicaltriasl.gov.# NCT01545167

Conflict of Interest: None of the authors had any financial relationship with any organization that sponsored the research.

References

  • 1.Mullady DK, Yadav D, Amann ST, et al. Type of pain, pain-associated complications, quality of life, disability and resource utilisation in chronic pancreatitis: a prospective cohort study. Gut. 2011;60:77–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Whitcomb DC, Larusch J, Krasinskas AM, et al. Common genetic variants in the CLDN2 and PRSS1-PRSS2 loci alter risk for alcohol-related and sporadic pancreatitis. Nature genetics. 2012;44:1349–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Whitcomb DC, Frulloni L, Garg P, et al. Chronic pancreatitis: An international draft consensus proposal for a new mechanistic definition. Pancreatology. 2016;16:218–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Amann ST, Yadav D, Barmada MM, et al. Physical and mental quality of life in chronic pancreatitis: a case-control study from the North American Pancreatitis Study 2 cohort. Pancreas. 2013;42:293–300. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Cote GA, Yadav D, Abberbock JA, et al. Recurrent Acute Pancreatitis Significantly Reduces Quality of Life Even in the Absence of Overt Chronic Pancreatitis. Am J Gastroenterol. 2018;113:906–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Machicado JD, Amann ST, Anderson MA, et al. Quality of Life in Chronic Pancreatitis is Determined by Constant Pain, Disability/Unemployment, Current Smoking, and Associated Co-Morbidities. Am J Gastroenterol. 2017;112:633–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Whitcomb DC, North American Pancreatitis Study G. Pancreatitis: TIGAR-O Version 2 Risk/Etiology Checklist With Topic Reviews, Updates, and Use Primers. Clin Transl Gastroenterol. 2019;10:e00027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Zator Z, Whitcomb DC. Insights into the genetic risk factors for the development of pancreatic disease. Therap Adv Gastroenterol. 2017;10:323–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Masamune A, Kotani H, Sorgel FL, et al. Variants That Affect Function of Calcium Channel TRPV6 Are Associated With Early-onset Chronic Pancreatitis. Gastroenterology. 2020;158:1626–41. [DOI] [PubMed] [Google Scholar]
  • 10.Goodarzi MO, Nagpal T, Greer P, et al. Genetic Risk Score in Diabetes Associated With Chronic Pancreatitis Versus Type 2 Diabetes Mellitus. Clin Transl Gastroenterol. 2019;10:e00057. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Bellin MD, Whitcomb DC, Abberbock J, et al. Patient and Disease Characteristics Associated With the Presence of Diabetes Mellitus in Adults With Chronic Pancreatitis in the United States. Am J Gastroenterol. 2017;112:1457–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Rickels MR, Bellin M, Toledo FG, et al. Detection, evaluation and treatment of diabetes mellitus in chronic pancreatitis: recommendations from PancreasFest 2012. Pancreatology. 2013;13:336–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Klein AP, Wolpin BM, Risch HA, et al. Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer. Nature communications. 2018;9:556. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Chen F, Childs EJ, Mocci E, et al. Analysis of Heritability and Genetic Architecture of Pancreatic Cancer: A PanC4 Study. Cancer Epidemiol Biomarkers Prev. 2019;28:1238–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Stoffel EM, McKernin SE, Brand R, et al. Evaluating Susceptibility to Pancreatic Cancer: ASCO Provisional Clinical Opinion. J Clin Oncol. 2019;37:153–64. [DOI] [PubMed] [Google Scholar]
  • 16.Shelton CA, Grubs RE, Umapathy C, et al. Impact of hereditary pancreatitis on patients and their families. J Genet Couns. 2020;(in press) Online ahead of print. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Whitcomb DC, Shelton C, Brand RE. Genetics and Genetic Testing in Pancreatic Cancer. Gastroenterology. 2015;149:1252–64. [DOI] [PubMed] [Google Scholar]
  • 18.Navratilova E, Morimura K, Xie JY, et al. Positive emotions and brain reward circuits in chronic pain. J Comp Neurol. 2016;524:1646–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Singh VV, Toskes PP. Medical therapy for chronic pancreatitis pain. Curr Gastroenterol Rep. 2003;5:110–6. [DOI] [PubMed] [Google Scholar]
  • 20.WHO. Depression [Web]. World Health Organization; 2018. [updated 22 March 2018; cited 2019]. Available from: https://www.who.int/news-room/fact-sheets/detail/depression. [Google Scholar]
  • 21.Otte C, Gold SM, Penninx BW, et al. Major depressive disorder. Nat Rev Dis Primers. 2016;2:16065. [DOI] [PubMed] [Google Scholar]
  • 22.Sullivan PF, Geschwind DH. Defining the Genetic, Genomic, Cellular, and Diagnostic Architectures of Psychiatric Disorders. Cell. 2019;177:162–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Howard DM, Adams MJ, Clarke TK, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Postolache TT, Del Bosque-Plata L, Jabbour S, et al. Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome. Am J Med Genet B Neuropsychiatr Genet. 2019;180:186–203. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Lee CH, Giuliani F. The Role of Inflammation in Depression and Fatigue. Front Immunol. 2019;10:1696. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Whitcomb DC, Yadav D, Adam S, et al. Multicenter approach to recurrent acute and chronic pancreatitis in the United States: the North American Pancreatitis Study 2 (NAPS2). Pancreatology. 2008;8:520–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Yadav D, Hawes RH, Brand RE, et al. Alcohol consumption, cigarette smoking, and the risk of recurrent acute and chronic pancreatitis. Arch Intern Med. 2009;169:1035–45. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Wilcox CM, Sandhu BS, Singh V, et al. Racial Differences in the Clinical Profile, Causes, and Outcome of Chronic Pancreatitis. Am J Gastroenterol. 2016;111:1488–96. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Conwell DL, Banks PA, Sandhu BS, et al. Validation of Demographics, Etiology, and Risk Factors for Chronic Pancreatitis in the USA: A Report of the North American Pancreas Study (NAPS) Group. Dig Dis Sci. 2017;62:2133–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Etemad B, Whitcomb DC. Chronic pancreatitis: Diagnosis, classification, and new genetic developments. Gastroenterology. 2001;120:682–707. [DOI] [PubMed] [Google Scholar]
  • 31.Whitcomb DC. Hereditary Pancreatitis: New insights into acute and chronic pancreatitis. Gut. 1999;45:317–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Stevens T, Conwell DL, Zuccaro G. Pathogenesis of chronic pancreatitis: an evidence-based review of past theories and recent developments. Am J Gastroenterol. 2004;99:2256–70. [DOI] [PubMed] [Google Scholar]
  • 33.Cote GA, Yadav D, Slivka A, et al. Alcohol and smoking as risk factors in an epidemiology study of patients with chronic pancreatitis. Clin Gastroenterol Hepatol. 2010;9:266–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Jeon CY, Whitcomb DC, Slivka A, et al. Lifetime Drinking History of Persons With Chronic Pancreatitis. Alcohol Alcohol. 2019;54:615–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Mullady DK, Yadav D, Amann ST, et al. Type of pain, pain-associated complications, quality of life, disability and resource utilisation in chronic pancreatitis: a prospective cohort study. Gut. 2011;60:77–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Wilcox CM, Yadav D, Tian Y, et al. Chronic Pancreatitis Pain Pattern and Severity are Independent of Abdominal Imaging Findings. Clin Gastroenterol Hepatol. 2014;13:552–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Romagnuolo J, Talluri J, Kennard E, et al. Clinical Profile, Etiology, and Treatment of Chronic Pancreatitis in North American Women: Analysis of a Large Multicenter Cohort. Pancreas. 2016;45:934–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Phillips AE, LaRusch J, Greer P, et al. Known genetic susceptibility factors for chronic pancreatitis in patients of European ancestry are rare in patients of African ancestry. Pancreatology. 2018;18:528–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.LaRusch J, Jung J, General IJ, et al. Mechanisms of CFTR functional variants that impair regulated bicarbonate permeation and increase risk for pancreatitis but not for cystic fibrosis. PLoS Genetics. 2014;10:e1004376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Schneider A, Larusch J, Sun X, et al. Combined Bicarbonate Conductance-Impairing Variants in CFTR and SPINK1 Variants Are Associated With Chronic Pancreatitis in Patients Without Cystic Fibrosis. Gastroenterology. 2011;140:162–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.LaRusch J, Lozano-Leon A, Stello K, et al. The Common Chymotrypsinogen C (CTRC) Variant G60G (C.180T) Increases Risk of Chronic Pancreatitis But Not Recurrent Acute Pancreatitis in a North American Population. Clin Transl Gastroenterol. 2015;6:e68. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Lowe ME, Andersen DK, Caprioli RM, et al. Precision Medicine in Pancreatic Disease-Knowledge Gaps and Research Opportunities: Summary of a National Institute of Diabetes and Digestive and Kidney Diseases Workshop. Pancreas. 2019;48:1250–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Whitcomb DC. Primer on Precision Medicine for Complex Chronic Disorders. Clin Transl Gastroenterol. 2019;10:e00067. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Shelton CA, Whitcomb DC. Precision medicine for pancreatic diseases Curr Opin Gastroenterol. 2020;(in press). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.McCarthy S, Das S, Kretzschmar W, et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016;48:1279–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Loh PR, Danecek P, Palamara PF, et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat Genet. 2016;48:1443–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Durbin R Efficient haplotype matching and storage using the positional Burrows-Wheeler transform (PBWT). Bioinformatics. 2014;30:1266–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Etemad B, Whitcomb DC. Chronic pancreatitis: Diagnosis, classification, and new genetic developments. Gastroenterology. 2001;120:682–707. [DOI] [PubMed] [Google Scholar]
  • 49.Gill SC, Butterworth P, Rodgers B, et al. Validity of the mental health component scale of the 12-item Short-Form Health Survey (MCS-12) as measure of common mental disorders in the general population. Psychiatry Res. 2007;152:63–71. [DOI] [PubMed] [Google Scholar]
  • 50.Vilagut G, Forero CG, Pinto-Meza A, et al. The mental component of the short-form 12 health survey (SF-12) as a measure of depressive disorders in the general population: results with three alternative scoring methods. Value Health. 2013;16:564–73. [DOI] [PubMed] [Google Scholar]
  • 51.R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2019. [Google Scholar]
  • 52.Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Buniello A, MacArthur JAL, Cerezo M, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 2019;47:D1005–D12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Pruim RJ, Welch RP, Sanna S, et al. LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics. 2010;26:2336–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Imanishi M Gapplin. 1.6.2 ed2019. [Google Scholar]
  • 56.Bair MJ, Robinson RL, Katon W, et al. Depression and pain comorbidity: a literature review. Arch Intern Med. 2003;163:2433–45. [DOI] [PubMed] [Google Scholar]
  • 57.McIntosh AM, Hall LS, Zeng Y, et al. Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis. PLoS Med. 2016;13:e1002090. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Sheng J, Liu S, Wang Y, et al. The Link between Depression and Chronic Pain: Neural Mechanisms in the Brain. Neural Plast. 2017;2017:9724371-. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Balliet WE, Edwards-Hampton S, Borckardt JJ, et al. Depressive Symptoms, Pain, and Quality of Life among Patients with Nonalcohol-Related Chronic Pancreatitis. Pain Res Treat. 2012;2012:978646. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Shah R, Haydek C, Mulki R, et al. Incidence and predictors of 30-day readmissions in patients hospitalized with chronic pancreatitis: A nationwide analysis. Pancreatology. 2018;18:386–93. [DOI] [PubMed] [Google Scholar]
  • 61.Fadista J, Manning AK, Florez JC, et al. The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants. Eur J Hum Genet. 2016;24:1202–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Wilcox CM, Yadav D, Ye T, et al. Chronic pancreatitis pain pattern and severity are independent of abdominal imaging findings. Clin Gastroenterol Hepatol. 2015;13:552–60; quiz e28-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.McIntosh AM, Sullivan PF, Lewis CM. Uncovering the Genetic Architecture of Major Depression. Neuron. 2019;102:91–103. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

Supplementary Information
NIHMS1803073-supplement-Supplementary_Information.docx (6.5MB, docx)

RESOURCES