Negative Self-Referent Cognition Predicts Future Depression Symptom Change: An Intensive Sampling Approach

Psycholog

Genetically predicted longer telomere length is associated with increased risk of B-cell lymphoma subtypes

Evidence from a small number of studies suggests that longer telomere length measured in peripheral leukocytes is associated with an increased risk of non-Hodgkin lymphoma (NHL). However, these studies may be biased by reverse causation, confounded by unmeasured environmental exposures and might miss time points for which prospective telomere measurement would best reveal a relationship between telomere length and NHL risk. We performed an analysis of genetically inferred telomere length and NHL risk in a study of 10 102 NHL cases of the four most common B-cell histologic types and 9562 controls using a genetic risk score (GRS) comprising nine telomere length-associated single-nucleotide polymorphisms. This approach uses existing genotype data and estimates telomere length by weighing the number of telomere length-associated variant alleles an individual carries with the published change in kb of telomere length. The analysis of the telomere length GRS resulted in an association between longer telomere length and increased NHL risk [four B-cell histologic types combined; odds ratio (OR) = 1.49, 95% CI 1.22–1.82, P-value = 8.5 × 10−5]. Subtype-specific analyses indicated that chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL) was the principal NHL subtype contributing to this association (OR = 2.60, 95% CI 1.93–3.51, P-value = 4.0 × 10−10). Significant interactions were observed across strata of sex for CLL/SLL and marginal zone lymphoma subtypes as well as age for the follicular lymphoma subtype. Our results indicate that a genetic background that favors longer telomere length may increase NHL risk, particularly risk of CLL/SLL, and are consistent with earlier studies relating longer telomere length with increased NHL risk

Genome-wide association study identifies multiple susceptibility loci for diffuse large B cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of three new genome-wide association studies (GWAS) and one prior scan, totaling 3,857 cases and 7,666 controls of European ancestry, with additional genotyping of nine promising SNPs in 1,359 cases and 4,557 controls. In our multi-stage analysis, five independent SNPs in four loci achieved genome-wide significance marked by rs116446171 at 6p25.3 (EXOC2; $P=2.33x10^{-21}$), rs2523607 at 6p21.33 (HLA-B; $2.40x10^{-10}$), rs79480871 at 2p23.3 (NCOA1; $P=4.23x10^{-8}$), and two independent SNPs, rs13255292 and rs4733601, at 8q24.21 (PVT1; $P=9.98x10^{-13}$ and $P=3.63x10^{-11}$, respectively). These data provide substantial new evidence for genetic susceptibility to this B-cell malignancy, and point towards pathways involved in immune recognition and immune function in the pathogenesis of DLBCL

Negative Self-Referent Cognition Predicts Future Depression Symptom Change: An Intensive Sampling Approach

Cognitive theories of depression assert that negative self-referent cognition has a causal role in the development and maintenance of depression symptoms, but few studies have examined temporal associations between these constructs using intensive, longitudinal sampling strategies. In three samples of undergraduate students, we examined associations between change in self-referent processing and depression across 5 daily assessments (Sample 1, N = 303, 1,194 measurements, 79% adherence), 7 daily assessments (Sample 2, N = 313, 1,784 measurements, 81% adherence), and 7 weekly assessments (Sample 3; N = 155, 833 measurements, 81% adherence). Random intercept cross-lagged panel models indicated large cross-lagged effects in two of the three samples (Samples 1 and 3 but not Sample 2), such that more negative self-referent thinking than usual was significantly associated with a subsequent increase in depression symptoms at the next time lag. Notably, change in depression from usual was not associated with increases in negative self-referent processing at the next time point in any sample. These findings suggest that change in negative self-referent processing may be causally linked to future increases in depression on a day-to-day and week-to week basis, although confidence in this conclusion is tempered somewhat by a lack of replication in Sample 2

Conversational Assessment Using Artificial Intelligence is as Clinically Useful as Depression Scales and Preferred by Users

This manuscript has been published at the Journal of Affective Disorders: https://doi.org/10.1016/j.jad.2024.01.212. Background: Depression is prevalent, chronic, and burdensome. Due to limited screening access, depression often remains undiagnosed. Artificial intelligence (AI) models based on spoken responses to interview questions may offer an effective, efficient alternative to other screening methods. Objective: The primary aim was to use a demographically diverse sample to validate an AI model, previously trained on human-administered interviews, on novel bot-administered interviews, and to check for algorithmic biases related to age, sex, race, and ethnicity. Methods: Using the Aiberry app, adults recruited via social media (N = 393) completed a brief bot-administered interview and a depression self-report form. An AI model was used to predict form scores based on interview responses alone. For all meaningful discrepancies between model inference and form score, clinicians performed a masked review to determine which one they preferred. Results: There was strong concurrent validity between the model predictions and raw self-report scores (r = 0.73, MAE = 3.3). 90% of AI predictions either agreed with self-report or with clinical expert opinion when AI contradicted self-report. There was no differential model performance across age, sex, race, or ethnicity. Limitations: Limitations include access restrictions (English-speaking ability and access to smartphone or computer with broadband internet) and potential self-selection of participants more favorably predisposed toward AI technology. Conclusion: The Aiberry model made accurate predictions of depression severity based on remotely collected spoken responses to a bot-administered interview. This study shows promising results for the use of AI as a mental health screening tool

Genome-wide association study identifies multiple susceptibility loci for diffuse large B cell lymphoma

Diffuse large B cell lymphoma (DLBCL) is the most common lymphoma subtype and is clinically aggressive. To identify genetic susceptibility loci for DLBCL, we conducted a meta-analysis of 3 new genome-wide association studies (GWAS) and 1 previous scan, totaling 3,857 cases and 7,666 controls of European ancestry, with additional genotyping of 9 promising SNPs in 1,359 cases and 4,557 controls. In our multi-stage analysis, five independent SNPs in four loci achieved genome-wide significance marked by rs116446171 at 6p25.3 (EXOC2; P = 2.33 × 10 '21), rs2523607 at 6p21.33 (HLA-B; P = 2.40 × 10 '10), rs79480871 at 2p23.3 (NCOA1; P = 4.23 × 10 '8) and two independent SNPs, rs13255292 and rs4733601, at 8q24.21 (PVT1; P = 9.98 × 10 '13 and 3.63 × 10 '11, respectively). These data provide substantial new evidence for genetic susceptibility to this B cell malignancy and point to pathways involved in immune recognition and immune function in the pathogenesis of DLBCL

Genetically predicted longer telomere length is associated with increased risk of B-cell lymphoma subtypes

Evidence from a small number of studies suggests that longer telomere length measured in peripheral leukocytes is associated with an increased risk of non-Hodgkin lymphoma (NHL). However, these studies may be biased by reverse causation, confounded by unmeasured environmental exposures and might miss time points for which prospective telomere measurement would best reveal a relationship between telomere length and NHL risk. We performed an analysis of genetically inferred telomere length and NHL risk in a study of 10 102 NHL cases of the four most common B-cell histologic types and 9562 controls using a genetic risk score (GRS) comprising nine telomere length-associated single-nucleotide polymorphisms. This approach uses existing genotype data and estimates telomere length by weighing the number of telomere length-associated variant alleles an individual carries with the published change in kb of telomere length. The analysis of the telomere length GRS resulted in an association between longer telomere length and increased NHL risk [four B-cell histologic types combined; odds ratio (OR) = 1.49, 95% CI 1.22-1.82,P-value = 8.5 × 10(-5)]. Subtype-specific analyses indicated that chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL) was the principal NHL subtype contributing to this association (OR = 2.60, 95% CI 1.93-3.51,P-value = 4.0 × 10(-10)). Significant interactions were observed across strata of sex for CLL/SLL and marginal zone lymphoma subtypes as well as age for the follicular lymphoma subtype. Our results indicate that a genetic background that favors longer telomere length may increase NHL risk, particularly risk of CLL/SLL, and are consistent with earlier studies relating longer telomere length with increased NHL risk