Late-Life Depressive Symptoms and Lifetime History of Major Depression: Cognitive Deficits are Largely Due to Incipient Dementia rather than Depression

Increasing variance of rich-club nodes distribution in early onset depression according to dynamic network

Early onset depression (EOD) and late onset depression (LOD) are thought to have different pathogeneses, but lack of pathological evidence. In the current study we describe the dynamic rich-club properties of patients with EOD and LOD to address this question indirectly. We recruited 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. Memory, executive function and processing speed were measured, and resting-stage functional MRI was performed with all participants. We constructed a dynamic functional connectivity network and carried out rich-club and modularity analyses. Normalized mutual information (NMI) was applied to describe the variance in rich-club nodes distribution and partitioning. The NMI coefficient of rich club nodes distribution among the three groups was the lowest in the EOD patients (F = 4.298; P = 0.0151, FDR = 0.0231), which was positively correlated with rich-club connectivity (R = 0.886, P < 0.001) and negatively correlated with memory (R = -0.347, P = 0.038) in the EOD group. In the LOD patients, non-rich-club connectivity was positively correlated with memory (R = 0.353, P = 0.030 and R = 0.420, P = 0.009). Furthermore, local connectivity was positively correlated with processing speed in the LOD patients (R = 0.374, P = 0.021). The modular partition was different between the EOD patients and the HCs (P = 0.0013 < 0.05/3). The temporal instability of rich-club nodes was found in the EOD patients, but not the LOD patients, supporting the hypothesis that EOD and LOD result from different pathogenesis, and showing that the instability of the rich-club nodes across time might disrupt rich-club connectivity.

Association of cognitive impairment with the interaction between chronic kidney disease and depression: findings from NHANES 2011-2014

BACKGROUND

Cognitive impairment (CoI), chronic kidney disease (CKD), and depression are prevalent among older adults and are interrelated, imposing a significant disease burden. This study evaluates the association of CKD and depression with CoI and explores their potential interactions.

METHOD

Data for this study were sourced from the 2011-2014 National Health and Nutritional Examination Survey (NHANES). Multiple binary logistic regression models assessed the relationship between CKD, depression, and CoI while controlling for confounders. The interactions were measured using the relative excess risk of interaction (RERI), the attributable proportion of interaction (AP), and the synergy index (S).

RESULTS

A total of 2,666 participants (weighted n = 49,251,515) were included in the study, of which 700 (16.00%) had CoI. After adjusting for confounding factors, the risk of CoI was higher in patients with CKD compared to non-CKD participants (odds ratio [OR] = 1.49, 95% confidence interval [CI]:1.12-1.99). The risk of CoI was significantly increased in patients with depression compared to those without (OR = 2.29, 95% CI: 1.73-3.03). Furthermore, there was a significant additive interaction between CKD and depression in terms of the increased risk of CoI (adjusted RERI = 2.01, [95% CI: 0.31-3.71], adjusted AP = 0.50 [95% CI: 0.25-0.75], adjusted S = 2.97 [95% CI: 1.27-6.92]).

CONCLUSION

CKD and depression synergistically affect CoI, particularly when moderate-to-severe depression co-occurs with CKD. Clinicians should be mindful of the combined impact on patients with CoI. Further research is needed to elucidate the underlying mechanisms and assess the effects specific to different CKD stages.

Distinguishing features of depression in dementia from primary psychiatric disease

Depression is a common and devastating neuropsychiatric symptom in the elderly and in patients with dementia. In particular, nearly 80% of patients with Alzheimer's Disease dementia experience depression during disease development and progression. However, it is unknown whether the depression in patients with dementia shares the same molecular mechanisms as depression presenting as primary psychiatric disease or occurs and persists through alternative mechanisms. In this review, we discuss how the clinical presentation and treatment differ between depression in dementia and as a primary psychiatric disease, with a focus on major depressive disorder. Then, we hypothesize several molecular mechanisms that may be unique to depression in dementia such as neuropathological changes, inflammation, and vascular events. Finally, we discuss existing issues and future directions for investigation and treatment of depression in dementia.

Comparing cardiovascular risk factors in older persons with mild cognitive impairment and lifetime history of major depressive disorder

OBJECTIVES

To compare the prevalence of select cardiovascular risk factors (CVRFs) in patients with mild cognitive impairment (MCI) versus lifetime history of major depression disorder (MDD) and a normal comparison group using baseline data from the Prevention of Alzheimer's Dementia with Cognitive Remediation plus Transcranial Direct Current Stimulation (PACt-MD) study.

DESIGN

Baseline data from a multi-centered intervention study of older adults with MCI, history of MDD, or combined MCI and history of MDD (PACt-MD) were analyzed.

SETTING

Community-based multi-centered study based in Toronto across 5 academic sites.

PARTICIPANTS

Older adults with MCI, history of MDD, or combined MCI and history of MDD and healthy controls.

MEASUREMENTS

We examined the baseline distribution of smoking, hypertension and diabetes in three groups of participants aged 60+ years in the PACt-MD cohort study: MCI (n = 278), MDD (n = 95), and healthy older controls (n = 81). Generalized linear models were fitted to study the effect of CVRFs on MCI and MDD as well as neuropsychological composite scores.

RESULTS

A higher odds of hypertension among the MCI cohort compared to healthy controls (p < .05) was noted in unadjusted analysis. Statistical significance level was lost on adjusting for age, sex and education (p > .05). A history of hypertension was associated with lower performance in composite executive function (p < .05) and overall composite neuropsychological test score (p < .05) among a pooled cohort with MCI or MDD.

CONCLUSIONS

This study reinforces the importance of treating modifiable CVRFs, specifically hypertension, as a means of mitigating cognitive decline in patients with at-risk cognitive conditions.

Adverse childhood experiences and cognitive function in adulthood: examining the roles of depressive symptoms and inflammation in a prospective cohort study

PURPOSE

Adverse childhood experiences (ACEs) have been associated with cognitive decline in adulthood. However, the underlying mechanisms implicated remain unclear. This study investigated depressive symptoms and systemic inflammation as potential mediators of the association between ACEs and later cognitive function.

METHODS

Participants were adults aged 50 + from the English Longitudinal Study of Ageing (N = 3029; 54.8% female). Measures included self-reported ACEs at wave 3 (2006-2007), C-reactive protein (CRP) and depressive symptoms at wave 4 (2008-2009), and cognitive function at waves 3 and 7 (2014-2015). Mediation analyses examined the direct associations between ACEs and cognitive function at wave 7 and the indirect associations via depressive symptoms and CRP at wave 4. In a first set of analyses, models were adjusted for sociodemographic factors and baseline cognitive function. In a second set of analyses, models were additionally adjusted for BMI and health behaviours (n = 1915).

RESULTS

Cumulative ACEs exposure positively predicted depressive symptoms (b = 0.184, s.e. = 0.034, p < .001), which in turn predicted poorer cognitive function at wave 7 (b =  - 0.035, s.e. = 0.008, p < .001). ACEs also positively predicted systemic inflammation as measured by CRP (b = 0.031, s.e. = 0.01, p = 0.0016). However, CRP did not mediate the association between ACEs and later cognitive function (b =  - 0.0002, 95% CI: - 0.002, 0.002).

CONCLUSION

These findings suggest that ACEs may be related to cognitive decline partly via depressive symptoms and corroborate prior research linking ACEs with systemic inflammation in adulthood.

Different Modular Organization Between Early Onset and Late Onset Depression: A Study Base on Granger Causality Analysis

Background: Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis.

Method: The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants.

Result: The Granger function network analysis suggested that the functional modularity was different among the three groups (P_auc = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD (P_auc = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient (P = 0.0002, P_fdr = 0.0744 & P = 0.0004, P_fdr = 0.0744).

Conclusion: This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD.

Late-Life Depressive Symptoms Are Associated With Functional Impairment Cross-sectionally and Over Time: Results of the AgeMooDe Study

OBJECTIVES

This study examines the relationship between late-life depressive symptoms, cognitive and functional impairment in a cohort of very old community-based participants.

METHODS

A sample of 1,226 primary care patients was assessed at baseline (Mage = 80.6 years). Statistical analyses were conducted using baseline and 12-month follow-up data.

RESULTS

At baseline, depressed participants showed minor cognitive deficits compared with nondepressed participants, whereas functional deficits were pronounced. Depressive symptoms and global cognition were not associated longitudinally. In contrast, follow-up functional impairment was predicted by baseline level and increase of depressive symptoms between baseline and follow-up. Reversely, follow-up depressive symptoms were predicted by functional decline between baseline and follow-up, whereas baseline functional status was not predictive.

DISCUSSION

Depressive symptoms and global cognitive function were not associated longitudinally, but level and increase of depressive symptoms over time predicted functional impairment after 1 year. Interventions to reduce depressive symptoms, or to encourage coping strategies might be promising to reduce functional impairment. Elevated follow-up depressive symptoms were only predicted by functional decline, supposedly emphasizing that incident functional impairment might be associated with an acute increase of depressive symptoms. Psychological adjustment processes were not examined, but might be targeted in future.

Risk of Dementia in persons who have previously experienced clinically-significant Depression, Anxiety, or PTSD: A Systematic Review and Meta-Analysis

BACKGROUND

Depression, anxiety and PTSD appear to be linked to dementia, but it is unclear whether they are risk factors (causal or prodromal) for, comorbid with, or sequelae to (secondary effect of) dementia. Existing meta-analyses have examined depression or anxiety in all-cause dementia, Alzheimer's disease (AD) and vascular dementia (VaD), but have not considered post-traumatic stress disorder (PTSD), dementia with Lewy bodies (DLB), or frontotemporal dementia (FTD). The current meta-analysis examined the risk of developing dementia (AD, VaD, DLB, FTD, all-cause) in people with and without a history of clinically-significant depression, anxiety or PTSD in order to better understand the link between mental illness and dementia (PROSPERO number: CRD42018099872).

METHODS

PubMed, EMBASE, PsycINFO and CINAHL searches identified 36 eligible studies.

RESULTS

There is a higher risk of developing all-cause dementia and AD in people with previous depression, and a higher risk of all-cause dementia in people with prior anxiety, than in persons without this history. Prior PTSD was not associated with a higher risk of later being diagnosed with dementia.

LIMITATIONS

The data for anxiety, PTSD, DLB and FTD were limited.

CONCLUSIONS

Depression and anxiety appear to be risk factors for dementia, but longitudinal studies across adulthood (young adult/mid-life/older adult) are needed to evaluate the likely causal or prodromal nature of this risk. The link between PTSD and dementia remains unclear. Regular screening for new onset mental illness and for cognitive changes in older adults with a history of mental illness may assist with earlier identification of dementia.

Determining the effects of LLD and MCI on brain decline according to machine learning and a structural covariance network analysis

BACKGROUND

Late-life depression (LLD) and mild cognitive impairment (MCI) are risk factors for Alzheimer disease (AD). However, the interactive effect between LLD and MCI in the progression to AD remains unknown. The purpose of this research is to clarify whether this interaction exists and determined the characteristics of the structural change patterns in LLD and MCI.

METHOD

To address this question, a total 225 participants (91 with intact cognitive function (IC), 34 with MCI, 35 with LLD-IC, 47 with LLD-MCI and 18 with AD) were recruited for the current study and their T1 scanning were acquired. Machine learning was applied to estimate the brain's age gap according to grey matter information (thickness and volume was calculated based on the Human Connectome Project Multi-Modal Parcellation version 1.0 and the Desikan atlas). A structural covariance network (SCN) was constructed based on grey matter volume. Rich-club analysis, global network properties and the Jaccard distance were utilized to describe the topological features in each cohort. Their cognitive functions (executive function, processing speed and memory) were evaluated by a full-scale battery of neuropsychological tests.

RESULT

The interactive effect between LLD and MCI was detected through the brain age gap. The estimated age was positively correlated with processing speed and memory in LLD and non-LLD subjects. In the SCN analysis, the rich-club coefficient and global network properties were disrupted in the MCI group, but remained normal in the LLD-IC, LLD-MCI and AD groups. There was a significant discrepancy in brain structural change patterns between the AD and other cohorts by the Jaccard distance.

CONCLUSION

The application of machine learning reflects that synergies between LLD and MCI could increase the risk of developing AD. According to the SCN, the structural coordination was disrupted in MCI and was kept normal in the other cohorts, while the discrepancies in brain structural change patterns appeared in AD. Overall, the brain age gap could be a potential predictor of AD, and the Jaccard distance has the potential to be a new type of SCN analysis indicator.

Clinical factors associated with progression to dementia in people with late-life depression: a cohort study of patients in secondary care

OBJECTIVES

Depression can be a prodromal feature or a risk factor for dementia. We aimed to investigate which clinical factors in patients with late-life depression are associated with a higher risk of developing dementia and a more rapid conversion.

DESIGN

Retrospective cohort study.

SETTING

South London and Maudsley NHS Foundation Trust (SLaM) secondary mental healthcare services.

PARTICIPANTS

The SLaM Clinical Record Interactive Search was used to retrieve anonymised data on 3659 patients aged 65 years or older who had received a diagnosis of depression in mental health services and had been followed up for at least 3 months.

OUTCOME MEASURES

Predictors of development of incident dementia were investigated, including demographic factors, health status rated on the Health of the National Outcome scale for older people (HoNOS65+), depression recurrence and treatments including psychotropic drugs and cognitive behavioural therapy (CBT).

RESULTS

In total, 806 (22.0%) patients developed dementia over a mean follow-up time of 2.7 years. Significant predictors of receiving a dementia diagnosis in fully adjusted models and after accounting for multiple comparisons were older age (adjusted HR=1.04, 95% CI 1.03 to 1.06 per year difference from sample mean) and the HoNOS65+ subscale measuring cognitive problems (HR=4.72, 95% CI 3.67 to 6.06 for scores in the problematic range). Recurrent depressive disorder or past depression (HR=0.65, 95% CI 0.55 to 0.77) and the receipt of CBT (HR=0.73 95% CI 0.61 to 0.87) were associated with a lower dementia risk. Over time, hazards related to age increased and hazards related to cognitive problems decreased.

CONCLUSIONS

In older adults with depression, a higher risk of being subsequently diagnosed with dementia was predicted by higher age, new onset depression, severity of cognitive symptoms and not receiving CBT. Further exploration is needed to determine whether the latter risk factors are responsive to interventions.

Cognitive impairment in depression: recent advances and novel treatments

In the past, little or no attention was paid to cognitive disorders associated with depression (a condition sometimes termed pseudodementia). However, recent years have seen a growing interest in these changes, not only because of their high frequency in acute-stage depression, but also because they have been found to persist, as residual symptoms (in addition to affective and psychomotor ones), in many patients who respond well to antidepressant treatment. These cognitive symptoms seem to impact significantly not only on patients' functioning and quality of life, but also on the risk of recurrence of depression. Therefore, over the past decade, pharmacological research in this field has focused on the development of new agents able to counteract not only depressive symptoms, but also cognitive and functional ones. In this context, novel antidepressants with multimodal activity have emerged. This review considers the different issues, in terms of disease evolution, raised by the presence of cognitive disorders associated with depression and considers, particularly from the neurologist's perspective, the ways in which the clinical approach to cognitive symptoms, and their interpretation to diagnostic and therapeutic ends, have changed in recent years. Finally, after outlining the pharmacodynamics and pharmacokinetics of the first multimodal antidepressant, vortioxetine, it reports the main results obtained with the drug in depressed patients, also in consideration of the ever-increasing evidence on its different mechanisms of action in animal models.

Kynurenine pathway changes in late-life depression with memory deficit

Kynurenine pathway (KP) activation is associated with many neuropsychiatric diseases, such as major depressive disorder (MDD) and Alzheimer's disease (AD). Investigations conducted on MDD seldom shed light on KP changes in late-life depression (LLD), though memory deficit (MD) in patients with LLD is a predictable sign of AD. Thus, we aimed to investigate whether tryptophan (TRP) metabolism and kynurenine (KYN) metabolism were imbalanced in patients with LLD with MD and in patients with LLD without MD. We explored KP characteristics between LLD with MD and LLD without MD groups. We investigated 85 patients with LLD and MD, 71 patients with LLD without MD, and 129 healthy controls (HCs). Serum concentrations of TRP, KYN, and kynurenic acid (KYNA) were detected by liquid chromatography-tandem mass spectrometry. Cognition performance was assessed by the Mini-Mental State Examination (MMSE). Language ability was assessed by the Boston Naming Test (BNT). Depressive symptoms were assessed by the 17-item Hamilton Depression Scale (HAMD-17). Lower TRP and KYNA levels, a lower KYNA/KYN ratio and a higher KYN/TRP ratio were found in patients with LLD and MD compared to those in HC. Low levels of TRP and KYN, in the absence of a changed KYN/TRP ratio, were found in patients with LLD without MD. The KYNA/TRP ratio and MMSE, BNT, and HAMD-17 scores were associated with the presence of LLD. MMSE scores and a trend for the KYN/TRP ratio were associated with the presence of MD in patients with LLD. Aside from MMSE scores, there was a trend toward an association between the KYN/TRP ratio and the presence of MD in patients with LLD. In conclusion, profound shifts in TRP metabolism and KYN metabolism were found in patients with LLD and MD but not in patients with LLD without MD.

Kynurenine pathway changes in late-life depression

BACKGROUND

Kynurenine pathway (KP) activation is associated with several neuropsychiatric diseases, including major depression disorder (MDD). Although several investigations have been conducted on MDD, these have seldom shed light on KP changes in late-life depression (LLD).

OBJECTIVE

We aimed to investigate whether tryptophan (TRP) metabolism and kynurenine (KYN) metabolism are imbalanced in LLD patients and to explore the differences in KP characteristics between early onset depression (EOD) and late onset depression (LOD) patients.

METHODS

We investigated 170 LLD patients (EOD 90, LOD 80) and 135 normal controls. Serum concentrations of TRP, KYN and kynurenic acid (KYNA) were detected by the liquid chromatography-tandem mass spectrometry method. Depressive symptoms were assessed by the 17-item Hamilton Depression Scale (HAMD-17).

RESULTS

LLD patients exhibited lower levels of TRP, KYN, KYNA and KYNA/KYN ratio and a higher level of KYN/TRY ratio than normal controls. The decrease in TRP and the increase in KYN/TRP ratio were found in LOD patients. A low TRP level without increased KYN/TRP ratio was found in EOD patients. The "Depression" factor, which was extracted from HAMD-17 by the principal component factor analysis, was correlated with the TRP level and KYNA/KYN ratio in the EOD group, but no such correlation was found in the LOD group.

CONCLUSIONS

KP changes were observed in LLD patients; LOD patients showed profound shifts in TRP metabolism, while EOD patients showed low TRP level and a shift in KYN metabolism.

The CERAD Neuropsychological Assessment Battery Is Sensitive to Alcohol-Related Cognitive Deficiencies in Elderly Patients: A Retrospective Matched Case-Control Study

OBJECTIVES

Adverse effects of heavy drinking on cognition have frequently been reported. In the present study, we systematically examined for the first time whether clinical neuropsychological assessments may be sensitive to alcohol abuse in elderly patients with suspected minor neurocognitive disorder.

METHODS

A total of 144 elderly with and without alcohol abuse (each group n=72; mean age 66.7 years) were selected from a patient pool of n=738 by applying propensity score matching (a statistical method allowing to match participants in experimental and control group by balancing various covariates to reduce selection bias). Accordingly, study groups were almost perfectly matched regarding age, education, gender, and Mini Mental State Examination score. Neuropsychological performance was measured using the CERAD (Consortium to Establish a Registry for Alzheimer's Disease). Classification analyses (i.e., decision tree and boosted trees models) were conducted to examine whether CERAD variables or total score contributed to group classification.

RESULTS

Decision tree models disclosed that groups could be reliably classified based on the CERAD variables "Word List Discriminability" (tapping verbal recognition memory, 64% classification accuracy) and "Trail Making Test A" (measuring visuo-motor speed, 59% classification accuracy). Boosted tree analyses further indicated the sensitivity of "Word List Recall" (measuring free verbal recall) for discriminating elderly with versus without a history of alcohol abuse.

CONCLUSIONS

This indicates that specific CERAD variables seem to be sensitive to alcohol-related cognitive dysfunctions in elderly patients with suspected minor neurocognitive disorder. (JINS, 2018, 24, 360-371).

Weight Rich-Club Analysis in the White Matter Network of Late-Life Depression with Memory Deficits

Patients with late-life depression (LLD) have a higher incident of developing dementia, especially individuals with memory deficits. However, little is known about the white matter characteristics of LLD with memory deficits (LLD-MD) in the human connectome, especially for the rich-club coefficient, which is an indicator that describes the organization pattern of hub in the network. To address this question, diffusion tensor imaging of 69 participants [15 LLD-MD patients; 24 patients with LLD with intact memory (LLD-IM); and 30 healthy controls (HC)] was applied to construct a brain network for each individual. A full-scale battery of neuropsychological tests were used for grouping, and evaluating executive function, processing speed and memory. Rich-club analysis and global network properties were utilized to describe the topological features in each group. Network-based statistics (NBS) were calculated to identify the impaired subnetwork in the LLD-MD group relative to that in the LLD-IM group. We found that compared with HC participants, patients with LLD (LLD-MD and LLD-IM) had relatively impaired rich-club organizations and rich-club connectivity. In addition, LLD-MD group exhibited lower feeder and local connective average strength than LLD-IM group. Furthermore, global network properties, such as the shortest path length, connective strength, efficiency and fault tolerant efficiency, were significantly decreased in the LLD-MD group relative to those in the LLD-IM and HC groups. According to NBS analysis, a subnetwork, including right cognitive control network (CCN) and corticostriatal circuits, were disrupted in LLD-MD patients. In conclusion, the disease effects of LLD were prevalent in rich-club organization. Feeder and local connections, especially in the subnetwork including right CCN and corticostriatal circuits, were further impaired in those with memory deficits. Global network properties were disrupted in LLD-MD patients relative to those in LLD-IM patients.

MRI-Based Classification Models in Prediction of Mild Cognitive Impairment and Dementia in Late-Life Depression

Objective: Late-life depression (LLD) is associated with development of different types of dementia. Identification of LLD patients, who will develop cognitive decline, i.e., the early stage of dementia would help to implement interventions earlier. The purpose of this study was to assess whether structural brain magnetic resonance imaging (MRI) in LLD patients can predict mild cognitive impairment (MCI) or dementia 1 year prior to the diagnosis.

Methods: LLD patients underwent brain MRI at baseline and repeated clinical assessment after 1-year. Structural brain measurements were obtained using Freesurfer software (v. 5.1) from the T1W brain MRI images. MRI-based Random Forest classifier was used to discriminate between LLD who developed MCI or dementia after 1-year follow-up and cognitively stable LLD. Additionally, a previously established Random Forest model trained on 185 patients with Alzheimer’s disease (AD) vs. 225 cognitively normal elderly from the Alzheimer’s disease Neuroimaging Initiative was tested on the LLD data set (ADNI model).

Results: MCI and dementia diagnoses were predicted in LLD patients with 76%/68%/84% accuracy/sensitivity/specificity. Adding the baseline Mini-Mental State Examination (MMSE) scores to the models improved accuracy/sensitivity/specificity to 81%/75%/86%. The best model predicted MCI status alone using MRI and baseline MMSE scores with accuracy/sensitivity/specificity of 89%/85%/90%. The most important region for all the models was right ventral diencephalon, including hypothalamus. Its volume correlated negatively with the number of depressive episodes. ADNI model trained on AD vs. Controls using SV could predict MCI-DEM patients with 67% accuracy.

Conclusion: LDD patients developing MCI and dementia can be discriminated from LLD patients remaining cognitively stable with good accuracy based on baseline structural MRI alone. Baseline MMSE score improves prediction accuracy. Ventral diencephalon, including the hypothalamus might play an important role in preservation of cognitive functions in LLD.