Hildebrandt, Michelle A.T.

Abstract Background: Mantle cell lymphoma (MCL) is an aggressive and rare B-cell non-Hodgkin lymphoma with poor prognosis, even with treatment. Despite its clinical importance, the etiology of MCL remains largely unknown. Some studies have reported a positive association with family history, suggesting that genetic factors could contribute to risk. Methods: To identify germline genetic variants associated with risk, we conducted the first genome-wide association studies (GWAS) and GWAS meta-analysis for MCL, comprising 1,163 cases and 61,271 controls. The most significant loci were taken forward for replication in three independent studies, including 576 cases and 771,773 controls. To identify potential target genes and pathways of discovered loci, we conducted F-MAGMA, colocalization, and transcriptome-wide association study (TWAS) analyses. To gain insight into underlying regulatory mechanisms, we performed integrative epigenomic analyses using DNase I hotspots and histone mark ChIP-seq data across diverse cell types applying the FORGE2 framework. Results: In the joint analyses, we identified eight genome-wide significant loci (P<5x10-8) associated with MCL risk, several of which were located near genes with known DNA repair (ATM), telomere (TERT), or RNA-binding functions (RBM20). Further analyses using F-MAGMA, which uses DNase-seq data to prioritize genes from GWAS, identified genes that were significantly associated with risk, including SP140, a chromatin reader and immune regulator of pathogen response. This gene also displayed strong colocalization with our lead variant in whole blood (COLOC posterior probability PP4=0.97). TWAS demonstrated significant associations with SP140 and ACTA2, which has been linked to cell proliferation (P<3x10-6). Enrichment for DNase I hotspots was observed in B and T lymphocytes (q-value<0.05), providing evidence for a role in immune cell-specific regulatory regions. Enrichment for enhancer-associated histone mark H3K4me1 was observed in B cells (q-value<0.01), highlighting a role for immune cell-specific enhancers. Transcription factor (TF) motif enrichment analysis pointed to TFs critical for B-cell development and differentiation, notably TCF3 and EP300 (q<0.01 for both), suggesting an association between B-cell lineage regulation and MCL risk. Finally, genome-wide SNP-based heritability was estimated to be 17%, underscoring the importance of common variants in MCL risk. Conclusion: Our study provides novel insight into the inherited susceptibility of MCL by identifying eight significant loci and estimating substantial common variant heritability. These findings highlight a role for several distinct biological pathways -specifically DNA repair, telomerase function, and B-cell differentiation- in the etiology of MCL, offering new targets for mechanistic investigation. Citation Format: Charles E. Breeze, Alyssa Clay-Gilmour, Hanla A. Park, Ólafur B. Davíðsson, Angelica Macauda, Brenda M. Birmann, Elizabeth E. Brown, Murat Güler, Michelle A. T. Hildebrandt, Alexandra Nieters, Krystle Ong, Jojo Biel-Nielsen Dietz, Karin E. Smedby, Karl Smith-Byrne, Rosalie Griffin, Sophia S. Wang, Susan Slager, James R. Cerhan, Jonathan N. Hofmann, Qing Lan, Nathaniel Rothman, Ingrid Glimelius, Henrik Hjalgrim, James Mckay, Sonja I. Berndt. Genome-wide association study of mantle cell lymphoma identifies novel loci suggesting a critical role for B-cell chromatin readers and DNA repair mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3602.

Summary Evidence for an association between insulin‐like growth factors (IGF) and multiple myeloma (MM) is inconsistent. We examined total IGF‐I concentrations and risk of MM by combining baseline serological data among UK Biobank participants ( n = 444 187; 732 incident MM) with a two‐sample Mendelian randomisation (MR) analysis using identified genetic variants associated with circulating total IGF‐I and IGF‐binding protein 3 (IGFBP‐3) in the InterLymph consortium (2434 MM and their 2567 controls). Finally, additional lymphoid neoplasm (LN) subtypes were included for comparison with the main hypothesis. Circulating IGF‐I level was positively associated with MM risk Hazard ratio‐HR‐per one standard deviation‐SD‐increase (HR 1‐SD = 1.11, 95% confidence interval [CI]: 1.01–1.22; p ‐value = 0.03), especially closer to diagnosis. Genetically inferred IGF‐I levels were associated with increased MM risk (odds ratio [OR] = 1.27, 95% CI: 1.05–1.54) but not with any other LNs. Genetically inferred IGFBP‐3 levels showed no associations with any LN evaluated. Corroborating previous findings, in a secondary analysis, IGF‐I levels were associated with the risk of chronic lymphocytic leukaemia/small lymphocytic lymphoma (CLL/SLL) in males with higher body mass index (HR 1‐SD in obese male = 1.36, 95% CI: 1.14–1.61). Our serological and MR analyses suggest a contributing role of IGF‐I in the susceptibility of MM; the CLL/SLL findings warrant further investigation considering sex‐specific adiposity.

Abstract Monoclonal gammopathy of undetermined significance (MGUS) is a necessary precursor condition to multiple myeloma (MM). Given the role of autophagy in modulating MM risk, we investigated whether genetic variation in autophagy‐related genes influences susceptibility to MGUS. We analyzed the association of 34,042 common autophagy‐related single nucleotide polymorphisms (SNPs) with MGUS across six independent cohorts, five from Europe and one from North America, comprising 2317 MGUS cases and 282,358 controls. We also assessed their impact on immune parameters, including absolute counts of 91 blood‐derived immune cell subsets and 103 circulating immunological proteins. Meta‐analysis revealed a genome‐wide significant association between the ULK4 rs6599175C allele and increased MGUS risk ( p = 3.35 × 10 −8 ). Carriers of this allele showed reduced counts of memory B cell subsets (IgM+CD38+CD27+ and IgD+IgM+CD27+; p = .0038 and p = .0056, respectively) and natural effector B cells (CD24+CD38+IgD+IgM+ cells; p = .0060). Although these associations were not statistically significant after multiple testing correction, they suggest a role of ULK4 in early B‐cell differentiation. Additionally, the CDKN2A rs2811710 variant showed a suggestive association with MGUS risk ( p = 2.17 × 10 −4 ), affecting transcription factor binding involved in B‐cell proliferation and differentiation, although it lacked association with immune markers. In conclusion, we confirm a genome‐wide significant association of the ULK4 locus and MGUS risk, supporting its role in early B‐cell differentiation, and identify CDKN2A as a candidate susceptibility locus warranting further investigation.

Abstract Background: Rural/nonmetropolitan (nonmetro) counties face known barriers to comprehensive cancer care compared with metropolitan (metro) counties, which may impact the outcomes for lymphoma patients. We evaluated the impact metro vs nonmetro status on outcomes after a diagnosis of non-Hodgkin lymphoma (NHL) in the context of clinical, demographic, and lifestyle factors. Methods: Of 7724 participants enrolled in the prospective LEO cohort study from 2015-2020, 7610 (98.5%) had their county of residence at diagnosis assigned a RUCC (2013) code. We compared outcomes of participants from metro (defined as RUCC 1-3, which are central counties with ≥1 urban areas of ≥50,000) vs nonmetro counties (RUCC 4-9, which are counties with smaller urban areas as well as completely rural). We estimated hazard ratios (HRs) and 95% confidence intervals (CI) from univariable and multivariable Cox models for associations of metro status with overall survival (OS). Cause of death (lymphoma [including treatment related], non-lymphoma, unknown) was assessed using a competing risk approach. Results: Compared with metro counties (N=6096), LEO participants from nonmetro counties (N=1514) were older (median age 64 vs 62 years; p<0.001), more likely to be non-Hispanic white (94% vs 75%; p<0.001) and married (84% vs 75%; p<0.001), and less likely to have completed graduate or professional school education (16% vs 27%; p<0.001). There were no notable differences (>5%) by metro status for sex, employment status, NHL subtype, stage, performance status, abnormal lactate dehydrogenase (LDH), international prognostic index (IPI), number of comorbidities, time from diagnosis to treatment interval (DTI) or participation in a clinical trial. Compared with LEO participants from metro counties, those from nonmetro counties had inferior OS at 5 years (74.5% vs 78.4%; HR=1.23, CI 1.10-1.37; p<0.001). The OS association only slightly attenuated after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.20, CI 1.07-1.34; p=0.002), and held in models that adjusted for clinical prognostic factors (stage, NHL subtype, IPI, DTI), socioeconomic status (SES; education, marital status), health status (comorbidity, frailty), or lifestyle factors (smoking, body mass index). Using a competing risk model, the cumulative incidence of death at 5 years due to lymphoma (16.9% vs 14.1%; p=0.002) and non-lymphoma (5.9% vs 3.9%; p=0.002) was higher for participants from nonmetro vs metro counties, respectively. For participants <65 years, nonmetro vs metro status had inferior OS (HR=1.40, CI 1.17-1.67; p<0.001). This association remained after adjustment for age, sex, race/ethnicity and NHL subtype (HR=1.36, CI 1.14-1.63; p<0.001), as well as after adjustment for clinical prognostic, SES, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was higher in participants from nonmetro vs metro counties (15.1% vs 11.5%; p=0.002), while there was no difference by metro status for non-lymphoma related deaths (2.1% vs 1.7%; p=0.47). In contrast, for participants age 65+ years, there was no differences by metro status for OS (HR=1.04, CI 0.91-1.20; p=0.56). After adjustment for age, sex, race/ethnicity and NHL subtype, participants from nonmetro areas had inferior OS (HR=1.12, 0.97-1.29) although this was not statistically significant (p=0.13), and was attenuated in models adjusting for clinical, health status, or lifestyle factors. The cumulative incidence of death at 5 years due to lymphoma was no different in participants from nonmetro vs metro counties (18.9% vs 18.0%; p=0.37), while non-lymphoma related deaths were higher in nonmetro counties (9.9% vs 6.8%; p=0.017). Conclusion: LEO participants from nonmetro vs metro counties had inferior OS overall, although this was predominately observed for younger (<65 years) participants. These associations did not appear to be explained by demographic, NHL subtype, clinical, SES, health status, or lifestyle factors. Of particular note, the risk of death due to lymphoma was higher in nonmetro areas for participants <65 years but not those 65+ years, while the risk of death due to other causes was higher in nonmetro areas for participants 65+ years but not those <65 years. These findings require further study, particularly related to barriers to care, and suggest the potential need for age-specific strategies to optimize outcomes for NHL patients from nonmetro/rural areas.

Src homology 2-domain containing protein tyrosine phosphatase 2 (SHP2), encoded by the Ptpn11 gene (Tyrosine-protein phosphatase non-receptor type 11), is a key downstream effector of PD-1/PD-L1 signaling and is likely important, in addition to immune modulation, in tumor development and vascular homeostasis. SHP2 conveys PD-1 mediated inhibitory signaling in T cells, and is emerging as a therapeutic target. Importantly, there is an association between immune checkpoint inhibitors (ICIs), immune-related adverse events (irAEs), and cardiovascular complications, underscoring the need to understand SHP2’s role in these processes. This review aims to summarize current knowledge on SHP2/PTPN11 biology, its role in immune regulation, cancer progression, and vascular homeostasis, and to discuss emerging therapeutic strategies targeting this pathway. The concept of using SHP2 inhibitors with immune checkpoint inhibitors (ICIs) is being investigated to address ICI resistance and to improve anti-tumor efficacy substantially. SHP2 is also being studied in non-cancer cell contexts, and signaling responses can differ by large magnitudes depending on the biological context and stimuli. Under normal circumstances, SHP2 promotes vascular homeostasis in endothelial cells (ECs) and myeloid cells and inhibits inflammation, and the reduction in SHP2 activity by oxidative stress, such as in atherosclerosis or diabetes, upregulates inflammation. In contrast, in response to radiation, the fibrotic response and subsequent lung injury were increased by endothelial SHP2 induction via Notch-Jag1 signaling. Vascular smooth muscle cells SHP2 act as a pro-atherogenic effector by enhancing ERK/MAPK signaling, and the upregulation of mitochondria localized SHP2 can also induce cellular senescence-associated inflammation by upregulating mitochondrial reactive oxygen species. Taken together, the two opposite signaling effects of SHP2 suggest that both the immune and vascular system responses appear to be more modulated by the redox, cell, and compartment-specific signaling of SHP2. More studies are needed for mitigating cardiovascular toxicity to patients, particularly with ICI-based treatment regimens.

ABSTRACT Newly diagnosed patients with non‐Hodgkin lymphoma (NHL) often have a history of other diseases, and these comorbidities can impact patient treatment and management options, as well as overall survival (OS). We developed the Lymphoma Epidemiology of Outcomes (LEO) comorbidity index (LCI) as a sum of 10 comorbidities adapted from the Self‐Report‐Generated Charlson Comorbidity Index (SRG‐CCI) for use in the LEO cohort, a national prospective study of newly diagnosed NHL. Of the 5502 participants with self‐reported comorbidity data, 3107 (56.4%) were male and the mean age at diagnosis was 60.9 years (range, 18–99 years). The LCI ranged from 0 to 6, with 48.6% having 0, 30.2% having 1, 21.2% having 2 or more comorbidities. With a median follow‐up of 62.4 months among surviving participants, 2099 patients had an event and 1219 died. Continuous LCI similarly predicted both 1‐year mortality (c‐statistic = 0.654) and OS (c‐statistic = 0.655), while it showed a weaker but still statistically significant predictive ability for lymphoma‐specific (c‐statistics = 0.617) and event‐free (c‐statistic = 0.574) survival. Participants with 1 (HR = 1.21, 95% CI 1.05–1.39) and 2+ (HR = 1.80, 95% CI 1.56–2.08) comorbidities had inferior OS compared to those with no comorbidities after adjustment for age and sex (c‐statistic = 0.654), and performance strengthened after adjustment for the International Prognostic Index (c‐statistic = 0.672). LCI predicted OS most strongly in marginal zone (c‐statistics = 0.748) and weakest in T‐cell (c‐statistic = 0.579) lymphoma. The cumulative incidence of death due to lymphoma, lymphoma treatment, and other causes all increased with increasing comorbidities, with the greatest increase observed for death due to other causes. The LCI performs comparable to other published comorbidity indices, supporting its use in the LEO cohort to better model real‐world outcomes and more generally providing an approach to implementing comorbidity indices in cancer survivorship cohorts.

Abstract Introduction: With over 80, 000 new cases of non-Hodgkin's lymphoma (NHL) diagnosed annually, modifiable risk factors remain unclear. Circadian disruption, linked to cancers like breast and prostate, affects immune cells (e.g., natural killer cells and T-helper cells) by altering their trafficking and proliferation. Some studies (PMID: 30566672, 27611440) suggest long sleep may increase overall NHL risk, including a Mendelian randomization (MR) study (PMID: 32895918). However, no research has examined the causal relationship between sleep traits, including long sleep, and NHL risk, by subtypes. We hypothesize that sleep traits are causally associated with NHL subtypes in European populations, testing this using MR with data from the International Lymphoma Epidemiology Consortium (InterLymph). Methods: We conducted two-sample MR using genome-wide association studies (GWAS) summary data for sleep traits and NHL subtypes. Only independent, genome-wide significant (p < 5×10-8) Single Nucleotide Polymorphisms (SNPs) were selected as valid instruments, sourced from the UK Biobank. Sleep traits included chronotype (153 SNPs), insomnia (48 SNPs), sleep duration (78 SNPs), excessive daytime sleepiness (37 SNPs), short sleep (27 SNPs), and long sleep (8 SNPs). NHL subtype data were from InterLymph: follicular lymphoma (6, 508 cases / 64, 183 controls), mantle cell lymphoma (1, 169 cases / 61, 603 controls), Waldenstrom macroglobulinemia/lymphoplasmacytic lymphoma (WM/LPL: 1, 697 cases / 59, 333 controls), and chronic lymphocytic leukemia (8, 522 cases / 67, 653 controls). The primary analysis used inverse-variance weighted (IVW) random-effects, with MR-Egger for pleiotropy adjustment. Results: Using the IVW method, we did not identify any statistically significant causal association between sleep traits and the risk of NHL subtypes, but did yield several intriguing trends. Long sleep (sleep duration >= 9 h per night) showed a marginally increased NHL risk [Odds ratio (OR) range: 1.51 - 247.9] across each subtype. Short sleep (sleep duration < 7 h per night) showed a similar trend [OR range: 1.25 - 1.81], except for WM/LPL, where we noticed a negative trend. The confidence limit for long sleep was imprecise due to the small number of variants. We did not notice any significant directional horizontal pleiotropy or weak instrument bias. Conclusions: We found no conclusive evidence of a relationship between sleep traits and four NHL subtypes. However, we see suggestive trends of long and short sleep associated with higher risk of some NHL subtypes. These findings align with the previous studies, which showed long sleep was associated with higher risk of NHL overall. Future directions include expanding our analysis to additional NHL subtypes, generating polygenic risk scores, and conducting stratified analyses. Citation Format: Pankhil Shah, Brittany Crawford, Anwar Merchant, Brenda Birmann, Angelica Macauda, Michelle A. Hildebrandt, Aaron Norman, Neil E. Caporaso, Meredith Yeager, Michael Dean, Immaculata De Vivo, Lynn Goldin, Nicola J. Camp, Rosalie Griffin, Delphine Casabonne, Federico Canzian, Pelin Unal, Elad Ziv, Catherine R. Marinac, Alexandra Nieters, Stephen J. Chanock, Mitchell J. Machiela, Michael Conry, Charlie Zhong, Hanla A. Park, Simon Cheah, Jonathan N. Hofmann, Elizabeth E. Brown, Celine Vachon, Susan Slager, Sonja Berndt, Sophia S. Wang, Vijai Joseph, James McKay, Henrik Hjalgrim, Lara Sucheston-Campbell, Karl Smith-Byrne, Alyssa Clay-Gilmour. Association between sleep traits and risk of non-Hodgkin's lymphoma subtypes: a mendelian randomization study in the International Lymphoma Epidemiology (InterLymph) Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7415.

Background: Indolent non-Hodgkin lymphomas (iNHL) are incurable and disproportionately affect adults age >65 in whom frailty and functional impairment can impact disease management. The Vulnerable Elders Survey (VES-13) is a 13-item screening tool that incorporates age, self-rated health, physical function limitations, and functional disabilities to identify vulnerable older community-dwelling adults. Adults with a VES-13 score of >3 have a fourfold increased risk of death or functional decline over 2 years as compared to adults with a score <3 (Saliba et al, JAGS 2001). Our team previously showed that VES-13 >3 was associated with a higher risk of 1-year mortality in NHL (OR 3.26, 95% CI 2.15-4.96, Fama et al, ASH 2019), including in adults age <65. In this study, we determined whether VES-13 scores >3 were associated with quality of life (QOL) changes in adults with iNHL across the age spectrum. Methods: We used the Lymphoma Epidemiology of Outcomes (LEO) Cohort Study to identify adults enrolled from 2015-2020 with grade 1-3A follicular and marginal zone lymphoma (FL, MZL) who completed the VES-13 at enrollment and QOL surveys at enrollment and follow-up. The LEO Cohort Study enrolls participants within 6 months of diagnosis and collects information on disease status, QOL, health behaviors, and patient-reported functional assessment. For this analysis we included QOL measured using the Functional Assessment of Cancer Therapy-General (FACT-G) at years 1 and 2 post-enrollment. The FACT-G total score was the sum of 4 subscales (range): physical (PWB, 0-28), social/family (SFWB, 0-28), emotional (EWB, 0-24), and functional (FWB, 0-28) well-being. A higher FACT-G total score (range 0-108) indicated better overall QOL. VES-13 scores ranged from 0 (lowest risk for death or decline) to 10+ (highest risk). Generalized linear mixed models evaluated changes in QOL from baseline based on VES-13 score >3 (vulnerable) vs <3 (non-vulnerable), within groups by age at enrollment >65 and <65. Results: Our study included 1,186 participants: 42% age >65, 54% female, 84% non-Hispanic White, 10% Hispanic, 3.3% Black, and 1.4% Asian/Pacific Islander. Most (68%) were diagnosed with FL. FLIPI was high risk for 20%, and MALT-IPI was high risk for 23%. In the VES-13 <3 group, the mean (SD) baseline FACT-G total score was 86.5 (12.0), PWB 21.0 (3.5), SFWB 24.3 (4.3), EWB 18.8 (3.7), and FWB 22.3 (4.9). In the VES-13 >3 group, the mean (SD) baseline FACT-G total score was 70.4 (16.5), PWB 15.4 (5.6), SFWB 22.3 (5.5), EWB 17.5 (4.5), and FWB 15.3 (6.4); all significantly lower than the VES-13 >3 group (all p<0.01). In adults <65, 63 (9%) had a VES-13 >3, which was associated with a significant improvement from baseline in PWB at years 1 and 2 when compared to VES-13 <3 (changes in baseline PWB were 2.1, 2.9 for VES-13 >3 vs 0.2, 0.1 for VES-13 <3, all p<0.05). Similarly, we observed improvement in FWB from baseline at years 1 and 2 in the VES-13 >3 vs <3 group (2.4, 2.9 vs 0.4, -0.1, respectively all p<0.05). The VES-13 >3 group had a decline in their EWB at 1 year vs the VES <3 group (-0.5 vs 1.2, respectively, p=0.003). At year 2, total FACT-G improved from baseline in the VES-13 >3 group (5.6 for VES-13 >3 vs -0.5 for VES-13 <3, p=0.002). SFWB changes from baseline did not differ between groups. In adults >65, 83 (17%) had a VES-13 >3, which was associated with a significant improvement from baseline PWB (1.3, 1.5 for VES-13 >3 vs. 0.1, -0.1 for VES-13 <3), FWB (3.3, 2.2 for VES-13 >3 vs. 0.5, 0.1 for VES-13 <3), and total FACT-G score (5.2, 3.4 for VES-13 >3 vs. 1.0, -0.4 for VES-13 <3) when compared to VES-13 <3 at years 1 and 2 (all p<0.05). SFWB and EWB changes from baseline did not differ between groups. While there was improvement from baseline PWB and FWB in the VES-13 >3 group, QOL scores across all subscales remained below the VES-13 <3 group in the study period for both age groups. Statistical significance was maintained in models adjusted for baseline characteristics, including initial treatment strategy (observation, systemic, vs local) for both age groups. Conclusion: Although the vulnerable group reported worse QOL throughout the study period compared to the non-vulnerable group, survivors in the vulnerable group saw greater improvement in their physical and functional well-being at 1- and 2-years post-diagnosis. Additional analyses are underway to identify drivers of improvement in physical and functional well-being in vulnerable adults diagnosed with iNHL.

Introduction: Over 80,000 new cases of Non-Hodgkin's Lymphoma (NHL) are diagnosed annually, but modifiable risk factors are largely unknown. Circadian disruption has been identified as a risk factor for several cancers, including breast and prostate cancer, and affects immune cells such as Natural Killer (NK) cells and T-helper cells. Disruptions in circadian rhythms can lead to aberrant immune cell trafficking and proliferation. Despite this biological connection, evidence linking circadian disruptions to NHL remains inconclusive. Only single Mendelian Randomization (MR) study (PMID: 32895918) has explored the causal relationship between sleep traits and overall NHL risk, without examining NHL subtypes. Studies have shown distinct risk factor profiles among NHL subtypes. Therefore, this study aims to investigate the causal relationship between sleep traits and NHL subtypes in European populations using MR. Methods: We conducted a two-sample MR analyses using genome-wide association studies (GWAS) summary data on sleep traits and NHL subtypes. The GWAS summary statistics on sleep traits were obtained from publicly available UKBiobank datasets. The sleep traits analyzed included chronotype (N=449,734), insomnia (N=237,627), sleep duration (N=446,118), daytime sleepiness (N=452,071), short sleep (N=411,934), and long sleep (N=339,926). Only independent, genome-wide significant SNPs (p < 5×10-8) were considered as valid instruments. The NHL subtype-specific summary statistics came from the InterLymph including follicular lymphoma (FL: N=6,508 cases / 64,183 controls), mantle cell lymphoma (MCL: N=1,169 cases / 61,603 controls), and Waldenström macroglobulinemia/lymphoplasmacytic lymphoma (WM/LPL: N=1,697 cases / 59,333 controls). Our primary analysis used the random-effects inverse-variance weighted (IVW) method. In addition, we employed MR-Egger to adjust for directional pleiotropy. Heterogeneity in the MR results was evaluated with Cochran's Q statistic. Results: The IVW method did not identify any statistically significant causal association between sleep traits and the risk of NHL subtypes (FL,MCL,WM/LPL), but did yield several intriguing associations. Chronotype (early rising) showed a tendency towards a marginally an increased NHL risk across subtypes [Odds ratio (OR) range: 1.07 - 2.56]. Conversely, a decreased risk was noted for long sleep (≥ 9 hours vs. 7-8 hours) [OR range: 0.19 - 0.62], insomnia [OR range: 0.72 - 0.88], and short sleep (excludes MCL) [OR range: 0.12 - 0.72]. Confidence limit for long sleep was wide due to small number of variants (N=8). The MR-Egger regression analysis did not provide evidence of significant directional horizontal pleiotropy. The F-statistics for all sleep traits were greater than 10 indicating absences of weak instrument bias. Conclusions: Our study found no statistically significant associations between sleep traits and three NHL subtypes (FL, MCL, WM/LPL) in European populations. However, we observed potential influences of chronotype, long and short sleep, and insomnia on NHL risk. These findings align with and extend previous MR study by providing subtype-specific insights. Future directions include expanding our analysis to additional NHL subtypes, generating polygenic risk scores, and conducting stratified analyses using the InterLymph population. These efforts aim to further elucidate the complex relationship between sleep characteristics and NHL risk across diverse subtypes and populations.