Longitudinal trajectories of brain age in young individuals at familial risk of mood disorder

Background: Within young individuals, mood disorder onset may be related to changes in trajectory of brain structure development. To date, however, longitudinal prospective studies remain scarce and show partly contradictory findings, with a lack of emphasis on changes at the level of global brain patterns. Cross-sectional adult studies have applied such methods and show that mood disorders are associated with accelerated brain ageing. Currently, it remains unclear whether young individuals show differential brain structure ageing trajectories associated with onset of mood disorder and/or presence of familial risk. Methods: Participants included young individuals (15-30 years, 53%F) from the prospective longitudinal Scottish Bipolar Family Study with and without close family history of mood disorder. All were well at time of recruitment. Implementing a structural MRI-based brain age prediction model, we globally assessed individual trajectories of age-related structural change using the difference between predicted brain age and chronological age (brain-predicted age difference (brain-PAD)) at baseline and at 2-year follow-up. Based on follow-up clinical assessment, individuals were categorised into three groups: (i) controls who remained well (C-well, n = 93), (ii) high familial risk who remained well (HR-well, n = 74) and (iii) high familial risk who developed a mood disorder (HR-MD, n = 35). Results: At baseline, brain-PAD was comparable between groups. Results showed statistically significant negative trajectories of brain-PAD between baseline and follow-up for HR-MD versus C-well (β = -0.60, pcorrected < 0.001) and HR-well (β = -0.36, pcorrected = 0.02), with a potential intermediate trajectory for HR-well (β = -0.24 years, pcorrected = 0.06). Conclusions: These preliminary findings suggest that within young individuals, onset of mood disorder and familial risk may be associated with a deceleration in brain structure ageing trajectories. Extended longitudinal research will need to corroborate findings of emerging maturational lags in relation to mood disorder risk and onset.

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Longitudinal trajectories of brain age in young individuals at familial risk of mood disorder from the Scottish Bipolar Family Study

Wellcome Open Research ◽

10.12688/wellcomeopenres.15617.2 ◽

2020 ◽

Vol 4 ◽

pp. 206

Author(s):

Laura de Nooij ◽

Mathew A. Harris ◽

Emma L. Hawkins ◽

Toni-Kim Clarke ◽

Xueyi Shen ◽

...

Keyword(s):

Mood Disorder ◽

Brain Structure ◽

Family Study ◽

Familial Risk ◽

Age Difference ◽

Age Related ◽

Brain Ageing ◽

Prospective Longitudinal ◽

Brain Age

Background: Within young individuals, mood disorder onset may be related to changes in trajectory of brain structure development. To date, however, longitudinal prospective studies remain scarce and show partly contradictory findings, with a lack of emphasis on changes at the level of global brain patterns. Cross-sectional adult studies have applied such methods and show that mood disorders are associated with accelerated brain ageing. Currently, it remains unclear whether young individuals show differential brain structure aging trajectories associated with onset of mood disorder and/or presence of familial risk. Methods: Participants included young individuals (15-30 years, 53%F) from the prospective longitudinal Scottish Bipolar Family Study with and without close family history of mood disorder. All were well at time of recruitment. Implementing a structural MRI-based brain age prediction model, we globally assessed individual trajectories of age-related structural change using the difference between predicted brain age and chronological age (brain-predicted age difference (brain-PAD)) at baseline and at 2-year follow-up. Based on follow-up clinical assessment, individuals were categorised into three groups: (i) controls who remained well (C-well, n = 93), (ii) high familial risk who remained well (HR-well, n = 74) and (iii) high familial risk who developed a mood disorder (HR-MD, n = 35). Results: At baseline, brain-PAD was comparable between groups. Results showed statistically significant negative trajectories of brain-PAD between baseline and follow-up for HR-MD versus C-well (β = -0.60, pcorrected < 0.001) and HR-well (β = -0.36, pcorrected = 0.02), with a potential intermediate trajectory for HR-well (β = -0.24 years, pcorrected = 0.06). Conclusions: These preliminary findings suggest that within young individuals, onset of mood disorder and familial risk may be associated with a deceleration in brain structure aging trajectories. Extended longitudinal research will need to corroborate findings of emerging maturational lags in relation to mood disorder risk and onset.

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Longitudinal trajectories of brain age in young individuals at familial risk of mood disorder from the Scottish Bipolar Family Study

Wellcome Open Research ◽

10.12688/wellcomeopenres.15617.3 ◽

2020 ◽

Vol 4 ◽

pp. 206

Author(s):

Laura de Nooij ◽

Mathew A. Harris ◽

Emma L. Hawkins ◽

Toni-Kim Clarke ◽

Xueyi Shen ◽

...

Keyword(s):

Mood Disorder ◽

Brain Structure ◽

Family Study ◽

Brain Aging ◽

Familial Risk ◽

Age Difference ◽

Age Related ◽

Prospective Longitudinal ◽

Brain Age

Background: Within young individuals, mood disorder onset may be related to changes in trajectory of brain structure development. To date, however, longitudinal prospective studies remain scarce and show partly contradictory findings, with a lack of emphasis on changes at the level of global brain patterns. Cross-sectional adult studies have applied such methods and show that mood disorders are associated with accelerated brain aging. Currently, it remains unclear whether young individuals show differential brain structure aging trajectories associated with onset of mood disorder and/or presence of familial risk. Methods: Participants included young individuals (15-30 years, 53%F) from the prospective longitudinal Scottish Bipolar Family Study with and without close family history of mood disorder. All were well at time of recruitment. Implementing a structural MRI-based brain age prediction model, we globally assessed individual trajectories of age-related structural change using the difference between predicted brain age and chronological age (brain-predicted age difference (brain-PAD)) at baseline and at 2-year follow-up. Based on follow-up clinical assessment, individuals were categorised into three groups: (i) controls who remained well (C-well, n = 93), (ii) high familial risk who remained well (HR-well, n = 74) and (iii) high familial risk who developed a mood disorder (HR-MD, n = 35). Results: At baseline, brain-PAD was comparable between groups. Results showed statistically significant negative trajectories of brain-PAD between baseline and follow-up for HR-MD versus C-well (β = -0.60, pcorrected < 0.001) and HR-well (β = -0.36, pcorrected = 0.02), with a potential intermediate trajectory for HR-well (β = -0.24 years, pcorrected = 0.06). Conclusions: These preliminary findings suggest that within young individuals, onset of mood disorder and familial risk may be associated with a deceleration in brain structure aging trajectories. Extended longitudinal research will need to corroborate findings of emerging maturational lags in relation to mood disorder risk and onset.

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Trajectory of brain maturation in adolescent individuals at familial risk of mood disorder

10.1101/537951 ◽

2019 ◽

Author(s):

Laura de Nooij ◽

Mathew A. Harris ◽

Emma L. Hawkins ◽

Xueyi Shen ◽

Toni-Kim Clarke ◽

...

Keyword(s):

Mood Disorder ◽

Longitudinal Research ◽

Familial Risk ◽

Structural Mri ◽

Brain Maturation ◽

History Of ◽

The Difference ◽

Prospective Longitudinal ◽

Brain Age

AbstractBackgroundAccelerated biological ageing has been proposed as a mechanism underlying mood disorder, but has been predominantly studied cross-sectionally in adult populations. It remains unclear whether differential ageing/maturation trajectories emerge earlier in life, in particular during the neurodevelopmental period of adolescence, and whether they are associated with onset of mood disorder and/or presence of familial risk.MethodsParticipants were young individuals (16-25 years) from the prospective longitudinal Scottish Bipolar Family Study (SBFS) with and without family history of mood disorder. All were well at time of recruitment. Implementing a structural MRI-based brain age prediction model, individual maturational trajectories were captured by the difference between predicted brain age and chronological age (brain-PAD) at baseline and two-year follow-up. Based on clinical assessment at follow-up, individuals were categorised into three groups: (i) controls who remained well (C-well,n=94), (ii) high familial risk who remained well (HR-well,n=73) and (iii) high familial risk who developed a mood disorder (HR-MD,n=38).ResultsResults showed no differences in brain-PAD between groups at baseline or follow-up. However, we found negative trajectories of brain-PAD for HR-MD versus C-well (β= −0.68 years,p<.001) and versus HR-well (β= −0.38 years,p=.01), and for HR-well versus C-well (β= −0.30 years,p=.03).ConclusionsThese findings suggest that within young individuals, onset of mood disorder and familial risk may be associated with a deceleration in brain maturation trajectory. However, without significantly differential status of brain maturation at follow-up, extended longitudinal research will need to show whether this marks the emergence of maturational lag.

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Adipose tissue distribution from body MRI is associated with cross-sectional and longitudinal brain age in adults

10.1101/2021.04.08.21255106 ◽

2021 ◽

Author(s):

Dani Beck ◽

Ann-Marie G. de Lange ◽

Dag Alnæs ◽

Ivan I. Maximov ◽

Mads L. Pedersen ◽

...

Keyword(s):

Adipose Tissue ◽

Tissue Distribution ◽

Brain Structure ◽

Fat Distribution ◽

Cardiometabolic Health ◽

Cross Sectional ◽

Adipose Tissue Distribution ◽

Brain Ageing ◽

Brain Age

AbstractThere is an intimate body-brain connection in ageing, and obesity is a key risk factor for poor cardiometabolic health and neurodegenerative conditions. Although research has demonstrated deleterious effects of obesity on brain structure and function, the majority of studies have used conventional measures such as waist-to-hip ratio, waist circumference, and body mass index. While sensitive to gross features of body composition, such global anthropomorphic features fail to describe regional differences in body fat distribution and composition, and to determine visceral adiposity, which is related to a range of metabolic conditions. In this mixed cross-sectional and longitudinal design (interval mean and standard deviation = 19.7 ± 0.5 months), including 790 healthy individuals (mean (range) age = 46.7 (18-94) years, 53% women), we investigated cross-sectional body magnetic resonance imaging (MRI, n = 286) measures of adipose tissue distribution in relation to longitudinal brain structure using MRI-based morphometry and diffusion tensor imaging (DTI). We estimated tissue-specific brain age at two time points and performed Bayesian multilevel modelling to investigate the associations between adipose measures at follow-up and brain age gap (BAG) at baseline and follow-up. We also tested for interactions between BAG and both time and age on each adipose measure. The results showed credible associations between T1-based BAG and liver fat, muscle fat infiltration (MFI), and weight-to-muscle ratio (WMR), indicating older-appearing brains in people with higher measures of adipose tissue. Longitudinal evidence supported interaction effects between time and MFI and WMR on T1-based BAG, indicating accelerated ageing over the course of the study period in people with higher measures of adipose tissue. The results show that specific measures of fat distribution are associated with brain ageing and that different compartments of adipose tissue may be differentially linked with increased brain ageing, with potential to identify key processes involved in age-related transdiagnostic disease processes.

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Neuroimaging-based brain-age prediction of first-episode schizophrenia and the alteration of brain age after early medication

The British Journal of Psychiatry ◽

10.1192/bjp.2021.169 ◽

2021 ◽

pp. 1-8

Author(s):

Yi-Bin Xi ◽

Xu-Sha Wu ◽

Long-Biao Cui ◽

Li-Jun Bai ◽

Shuo-Qiu Gan ◽

...

Keyword(s):

Diffusion Tensor ◽

First Episode ◽

Age Difference ◽

Healthy Controls ◽

Data Set ◽

Brain Ageing ◽

First Episode Schizophrenia ◽

Brain Age ◽

The Brain ◽

Age Prediction

Background Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear. Aims To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age. Method The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed. Results The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = −0.326, P = 0.014). Conclusions The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.

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Choriocapillaris flow impairment could predict the enlargement of geographic atrophy lesion

British Journal of Ophthalmology ◽

10.1136/bjophthalmol-2019-315800 ◽

2020 ◽

Vol 105 (1) ◽

pp. 97-102 ◽

Cited By ~ 2

Author(s):

Riccardo Sacconi ◽

Eleonora Corbelli ◽

Enrico Borrelli ◽

Luigi Capone ◽

Adriano Carnevali ◽

...

Keyword(s):

Fundus Autofluorescence ◽

Control Area ◽

Geographic Atrophy ◽

Age Related Macular Degeneration ◽

Age Related ◽

Slow Progression ◽

Minimum Angle ◽

Perfusion Density ◽

Prospective Longitudinal

AimTo analyse the choriocapillaris (CC) flow status in the area that subsequently showed geographic atrophy (GA) expansion secondary to age-related macular degeneration (AMD) during 1-year follow-up, matching optical coherence tomography angiography (OCT-A) and fundus autofluorescence (FAF).MethodsIn this prospective longitudinal observational study, 30 eyes of 20 consecutive patients with GA secondary to AMD (mean age 75.5±7.4 years) were included. All patients underwent OCT-A and FAF at baseline and 1-year follow-up. Main outcome measures included analysis of perfusion density (PD) in the ‘area surrounding GA margin’ (between the GA border and 500 µm distance) in comparison with the ‘control area’ (area outside the 500 µm line), and of the ‘expansion area’ (area that subsequently developed GA expansion during 1-year follow-up).ResultsDuring the 1-year follow-up, visual acuity significantly decreased from 0.34±0.38 Logarithm of the Minimum Angle of Resolution (LogMAR) to 0.39±0.40 LogMAR (p<0.001), and mean GA area increased from 6.82±5.47 mm2 to 8.76±6.28 mm2 (p<0.001). CC PD of the area surrounding the GA margin revealed a significant flow impairment compared with control area (PD 0.679±0.076 and 0.734±0.057, respectively (p<0.001)). Furthermore, the PD of the expansion area showed a greater CC flow impairment in comparison to the remaining area surrounding GA margin (p<0.001).ConclusionsWe reported a greater CC impairment in the area that subsequently developed GA expansion, suggesting that the CC flow impairment could predict the enlargement of GA lesion. The CC impairment could be considered as a new a risk factor for GA progression and a biomarker to be measured to determine efficacy of new interventions aiming to slow progression of GA.

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Prospective longitudinal voxel-based morphometry study of major depressive disorder in young individuals at high familial risk

Psychological Medicine ◽

10.1017/s0033291716000519 ◽

2016 ◽

Vol 46 (11) ◽

pp. 2351-2361 ◽

Cited By ~ 13

Author(s):

T. Nickson ◽

S. W. Y. Chan ◽

M. Papmeyer ◽

L. Romaniuk ◽

A. Macdonald ◽

...

Keyword(s):

Major Depressive Disorder ◽

High Risk ◽

Depressive Disorder ◽

Mood Disorder ◽

Childhood Trauma ◽

Familial Risk ◽

Voxel Based Morphometry ◽

Major Depressive ◽

Potential Biomarker ◽

Prospective Longitudinal

BackgroundPrevious neuroimaging studies indicate abnormalities in cortico-limbic circuitry in mood disorder. Here we employ prospective longitudinal voxel-based morphometry to examine the trajectory of these abnormalities during early stages of illness development.MethodUnaffected individuals (16–25 years) at high and low familial risk of mood disorder underwent structural brain imaging on two occasions 2 years apart. Further clinical assessment was conducted 2 years after the second scan (time 3). Clinical outcome data at time 3 was used to categorize individuals: (i) healthy controls (‘low risk’, n = 48); (ii) high-risk individuals who remained well (HR well, n = 53); and (iii) high-risk individuals who developed a major depressive disorder (HR MDD, n = 30). Groups were compared using longitudinal voxel-based morphometry. We also examined whether progress to illness was associated with changes in other potential risk markers (personality traits, symptoms scores and baseline measures of childhood trauma), and whether any changes in brain structure could be indexed using these measures.ResultsSignificant decreases in right amygdala grey matter were found in HR MDD v. controls (p = 0.001) and v. HR well (p = 0.005). This structural change was not related to measures of childhood trauma, symptom severity or measures of sub-diagnostic anxiety, neuroticism or extraversion, although cross-sectionally these measures significantly differentiated the groups at baseline.ConclusionsThese longitudinal findings implicate structural amygdala changes in the neurobiology of mood disorder. They also provide a potential biomarker for risk stratification capturing additional information beyond clinically ascertained measures.

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Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

10.1101/2022.01.10.21267840 ◽

2022 ◽

Author(s):

Constantinos Constantinides ◽

Laura KM Han ◽

Clara Alloza ◽

Linda Antonucci ◽

Celso Arango ◽

...

Keyword(s):

Clinical Characteristics ◽

Large Scale ◽

Age Of Onset ◽

Collaborative Study ◽

Brain Magnetic Resonance Imaging ◽

Age Difference ◽

Intracranial Volume ◽

Age Related ◽

Brain Ageing ◽

Increased Risk

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.64 years (95% CI: 3.01, 4.26; I2 = 55.28%) compared to controls, after adjusting for age and sex (Cohen's d = 0.50). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

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The Association Between Poor Sleep and Accelerated Brain Ageing

10.1101/2021.06.16.448332 ◽

2021 ◽

Author(s):

Jivesh Ramduny ◽

Matteo Bastiani ◽

Robin Huedepohl ◽

Stamatios Sotiropoulos N Sotiropoulos ◽

Magdalena Chechlacz

Keyword(s):

Older Adults ◽

Sleep Quality ◽

Sleep Problems ◽

Sleep Fragmentation ◽

Poor Sleep ◽

Age Related ◽

Brain Ageing ◽

Neuroimaging Data ◽

Brain Age ◽

Ageing Brain

The ageing brain undergoes widespread gray (GM) and white matter (WM) degeneration. But numerous studies indicate large heterogeneity in the age-related brain changes, which can be attributed to modifiable lifestyle factors, including sleep. Inadequate sleep has been previously linked to GM atrophy and WM changes. However, the reported findings are highly inconsistent. By contrast to previous research independently characterizing patterns of either the GM or the WM changes, we used here linked independent component analysis (FLICA) to examine covariation in GM and WM in a group of older adults. Next, we employed a novel technique to estimate the brain age delta (i.e. difference between chronological and apparent brain age assessed using neuroimaging data) and study its associations with sleep quality and sleep fragmentation, hypothesizing that poor sleep accelerates brain ageing. FLICA revealed a number of multimodal (including both GM and WM) neuroimaging components, associated with age, but also with sleep quality and sleep fragmentation. Brain age delta estimates were highly sensitive in detecting the effects of sleep problems on the ageing brain. Specifically, we show significant associations between brain age delta and poor sleep quality, suggesting two years deviation above the chronological age. Our findings indicate that sleep problems in healthy older adults should be considered a risk factor for accelerated brain ageing.

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1195Brain-predicted age difference is associated with cognitive processing and delayed recall in later life

International Journal of Epidemiology ◽

10.1093/ije/dyab168.720 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Jo Wrigglesworth ◽

Nurathifah Yaacob ◽

Phillip Ward ◽

Robyn Woods ◽

John McNeil ◽

...

Keyword(s):

Community Dwelling ◽

Chronological Age ◽

Accelerated Ageing ◽

Age Difference ◽

Psychomotor Speed ◽

Delayed Recall ◽

Memory Decline ◽

Brain Ageing ◽

Community Dwelling Older Adults ◽

Brain Age

Abstract Background Brain age is a novel neuroimaging-based marker of ageing that uses machine learning to predict a person’s biological brain age. A higher brain age relative to chronological age (i.e., brain-predicted age difference [brain-PAD]) is considered a sign of accelerated ageing. We examined whether brain-PAD is associated with cognition and the change in cognitive function over time. Methods This study involved 531 cognitively healthy community-dwelling older adults (70+ years). Using a previously trained algorithm, brain age was estimated using T1-weighted structural magnetic resonance images acquired at baseline. Psychomotor speed, delayed recall, verbal fluency and global cognition were assessed at baseline, years 1 and 3. Results At baseline, a significant negative association was observed between brain-PAD and psychomotor speed (r=-0.14, p = 0.001), delayed recall (r=-0.09, p = 0.04), and the three-year change in delayed recall (r=-0.15, p = 0.02), which persisted after adjusting for covariates. Conclusions These findings indicate that accelerated brain ageing in cognitively unimpaired older people is associated with worse psychomotor speed, and delayed recall. This study also provides new evidence that accelerated brain ageing is a risk factor for progressive memory decline. Future research would benefit from further prospective analyses of associations between brain-PAD and cognitive function in community dwelling older adults. Key messages Brain age is a neuroimaging-based marker of biological ageing. A higher estimate of brain age relative to chronological age (i.e., accelerated ageing) is associated with worse psychomotor speed and memory, and memory decline.

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