Major depression and the biological hallmarks of aging

Lorenzo, Erica C; Kuchel, George A.; Kuo, Chia‐Ling; Moffitt, Terrie E.; Diniz, Breno S.

doi:10.1016/j.arr.2022.101805

Cited by 48 publications

(27 citation statements)

References 157 publications

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“…The anterior scalp distribution of the P300 latencies involved in these brain-behavior associations suggests that MDD symptoms may interfere with the speed of involuntary attention allocation to regularly presented stimuli, possibly indicating slower memory trace formation for the standard tones, resulting in less efficient stimulus categorization. These observations are consistent with prior reports of a compensatory frontal shift in the P300 topography in older adults (van Dinteren et al, 2018 ) and serve as additional evidence of potentially accelerated cognitive aging in MDD (see also Oi, 2017 ; Sacchet et al, 2017 ; Lorenzo et al, 2022 ).…”

Section: Discussionsupporting

confidence: 91%

“…Time since birth is the most readily available and therefore commonly used objective measure of age. However, prior studies (e.g., Han et al, 2018 ), as well as our results, suggest that patients with MDD may be biologically older than their chronological age, and the latest reports note a significant overlap between the biological alterations in MDD and those commonly observed in aging (Lorenzo et al, 2022 ). The lack of an objectively quantified biological age is a limitation of the current analysis.…”

Section: Discussionsupporting

confidence: 67%

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Electrophysiological biomarkers and age characterize phenotypic heterogeneity among individuals with major depressive disorder

Key

Thornton‐Wells

Smith

2023

Front. Hum. Neurosci.

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Introduction: Despite the high need for effective treatments for major depressive disorder (MDD), the development of novel medicines is hampered by clinical, genetic and biological heterogeneity, unclear links between symptoms and neural dysfunction, and tenuous biomarkers for clinical trial contexts of use.Methods: In this study, we examined the International Study to Predict Optimized Treatment in Depression (iSPOT-D) clinical trial database for new relationships between auditory event-related potential (ERP) responses, demographic features, and clinical symptoms and behavior, to inform strategies for biomarker-driven patient stratification that could be used to optimize future clinical trial design and drug development strategy in MDD.Results: We replicate findings from previous analyses of the classic auditory oddball task in the iSPOT-D sample showing smaller than typical N1 and P300 response amplitudes and longer P300 latencies for target and standard stimuli in patients with MDD, suggesting altered bottom-up sensory and top-down attentional processes. We further demonstrate that age is an important contributor to clinical group differences, affecting both topographic distribution of the clinically informative ERP responses and the types of the stimuli sensitive to group differences. In addition, the observed brain-behavior associations indicate that levels of anxiety and stress are major contributing factors to atypical sensory and attentional processing among patients with MDD, particularly in the older subgroups.Discussion: Our novel findings support the possibility of accelerated cognitive aging in patients with MDD and identify the frontal P300 latency as an additional candidate biomarker of MDD. These results from a large, well-phenotyped sample support the view that heterogeneity of the clinical population with MDD can be systematically characterized based on age and neural biomarkers of sensory and attentional processing, informing patient stratification strategies in the design of clinical trials.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 67%

Electrophysiological biomarkers and age characterize phenotypic heterogeneity among individuals with major depressive disorder

Key

Thornton‐Wells

Smith

2023

Front. Hum. Neurosci.

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“…Recent reports from multiple cohorts reveal poor mental health as a risk factor for more advanced and faster biological aging, including self-reported unsuccessful aging 3 , accelerated brain aging 4 , shorter leukocyte telomere length 5 , epigenetic aging measured from blood DNA methylation profiles 6 , and older biological age and faster pace of aging as measured from blood chemistries and other clinical traits 7 . However, nearly all work to date had focused on the hypothesis that poor mental health accelerates processes of biological aging 8 . A complementary, but less-studied hypothesis is that accelerated processes of biological aging may, themselves, pose risks to depression/anxiety disorders of older adults 9 .…”

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confidence: 99%

Accelerated biological aging and risk of depression and anxiety: evidence from 424,299 UK Biobank participants

et al. 2023

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Theory predicts that biological processes of aging may contribute to poor mental health in late life. To test this hypothesis, we evaluated prospective associations between biological age and incident depression and anxiety in 424,299 UK Biobank participants. We measured biological age from clinical traits using the KDM-BA and PhenoAge algorithms. At baseline, participants who were biologically older more often experienced depression/anxiety. During a median of 8.7 years of follow-up, participants with older biological age were at increased risk of incident depression/anxiety (5.9% increase per standard deviation [SD] of KDM-BA acceleration, 95% confidence intervals [CI]: 3.3%–8.5%; 11.3% increase per SD of PhenoAge acceleration, 95% CI: 9.%–13.0%). Biological-aging-associated risk of depression/anxiety was independent of and additive to genetic risk measured by genome-wide-association-study-based polygenic scores. Advanced biological aging may represent a potential risk factor for incident depression/anxiety in midlife and older adults and a potential target for risk assessment and intervention.

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“… 20 Moreover, age is a robust predictor of depression risk, 21 with numerous studies concentrating on depression in the elderly, 22 , 23 where research suggests a positive association between depression and age. 24 Further research delves into the area of subjective age and reveals that higher subjective age also poses a higher risk of depressive emotions. 25 , 26 …”

Section: Literature Reviewmentioning

confidence: 99%

The Nonlinear Relationship Between Body Mass Index (BMI) and Perceived Depression in the Chinese Population

Li¹,

Li²,

Liu³

et al. 2023

PRBM

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Purpose Existing studies on the association between BMI and depression report conflicting results with some demonstrating a positive relationship, while others a negative link or insignificant correlation. Very limited research on the nonlinear relationship between BMI and depression has yet to clarify the reliability and robustness of the potential nonlinearity and whether a more complex association exists. This paper aims to systematically investigate the nonlinear relationship between the two factors applying rigorous statistical methods, as well as explore the heterogeneity of their association. Materials and Methods A large-scale nationally representative dataset, Chinese General Social Survey, is used to empirically analyze the nonlinear relationship between BMI and perceived depression. Various statistical tests are employed to check the robustness of the nonlinearity. Results Results indicate that there is a U-shaped relationship between BMI and perceived depression, with the turning point (25.718) very close to while slightly larger than the upper limit of the range of healthy weight (18.500 ≤ BMI < 25.000) defined by World Health Organization. Both very high and low BMIs are associated with increased risk for depressive disorders. Furthermore, perceived depression is higher at almost all BMI levels among individuals who are older, female, lower educated, unmarried, in rural areas, belonging to ethnic minorities, non-Communist Party of China members, as well as those with lower income and uncovered by social security. In addition, these subgroups have smaller inflection points and their self-rated depression is more sensitive to BMI. Conclusion This paper confirms a significant U-shaped trend in the association between BMI and depression. Therefore, it is important to account for the variations in this relationship across different BMI categories when using BMI to predict depression risk. Besides, this study clarifies the management goals for achieving an appropriate BMI from a mental health perspective and identifies vulnerable subgroups at higher risk of depression.

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Major depression and the biological hallmarks of aging

Cited by 48 publications

References 157 publications

Electrophysiological biomarkers and age characterize phenotypic heterogeneity among individuals with major depressive disorder

Electrophysiological biomarkers and age characterize phenotypic heterogeneity among individuals with major depressive disorder

Accelerated biological aging and risk of depression and anxiety: evidence from 424,299 UK Biobank participants

The Nonlinear Relationship Between Body Mass Index (BMI) and Perceived Depression in the Chinese Population

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