Biology subjects

Salminen, L. E.

Publications and source records attributed to Salminen, L. E..

6 recordsLinked to original sources

bioRxiv2022

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup

BackgroundThe cerebellum critically contributes to higher-order cognitive and emotional functions such fear learning and memory. Prior research on cerebellar volume in PTSD is scant and has neglected neuroanatomical subdivisions of the cerebellum that differentially map on to motor, cognitive, and affective functions. MethodsWe quantified cerebellar lobule volumes using structural magnetic resonance imaging in 4,215 adults (PTSD n= 1640; Control n=2575) across 40 sites from the from the ENIGMA-PGC PTSD working group. Using a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation, we obtained volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum total and subregional volume in PTSD compared to healthy controls. The Benjamini-Hochberg procedure was used to control the false discovery rate (p-FDR < .05). ResultsPTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume. In addition, people with PTSD showed reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), but also the vermis (VI, VIII), flocculonodular lobe (lobule X), and cerebellar white matter (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. ConclusionsThese findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in high-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

neuroscience↗

bioRxiv2021

A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site- specific profiles in participants demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,343 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,067 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM were more sensitive to the detection of significant case-control differences in regional cortical thickness (X2(3) = 34.339, p < 0.001), and case-control differences in age-related cortical thinning (X2(3) = 15.128, p = 0.002). Specifically, ComBat-GAM led to larger effect size estimates of cortical thickness reductions (corrected p-values < 0.001), smaller age-appropriate declines (corrected p-values < 0.001), and lower female to male contrast (corrected p-values < 0.001) in cases compared to controls relative to other harmonization methods. Harmonization with ComBat-GAM also led to greater estimates of age-related declines in cortical thickness (corrected p-values < 0.001) in both cases and controls compared to other harmonization methods. Our results support the use of ComBat-GAM for harmonizing cortical thickness data aggregated from multiple sites and scanners to minimize confounds and increase statistical power.

neuroscience↗

bioRxiv2019

Hippocampal subfield volumes are uniquely affected in PTSD and depression: International analysis of 31 cohorts from the PGC-ENIGMA PTSD Working Group

BackgroundPTSD and depression commonly co-occur and have been associated with smaller hippocampal volumes compared to healthy and trauma-exposed controls. However, the hippocampus is heterogeneous, with subregions that may be uniquely affected in individuals with PTSD and depression.\n\nMethodsWe used random effects regressions and a harmonized neuroimaging protocol based on FreeSurfer (v6.0) to identify sub-structural hippocampal markers of current PTSD (C-PTSD), depression, and the interaction of these conditions across 31 cohorts worldwide (N=3,115; Mage=38.9{+/-}13.9 years). Secondary analyses tested these associations by sex and after modeling the simultaneous effects of remitted PTSD, childhood trauma, mild traumatic brain injury, and alcohol use disorder.\n\nResultsA significant negative main effect of depression (n=800, vs. no depression, n=1456) was observed in the hippocampal tail ({beta}=-0.13) and CA1 ({beta}=-0.09) after adjusting for covariates and multiple testing (adjusted ps (q)=0.028). A main effect of C-PTSD (n=1042 vs. control, n=1359) was not significant, but an interaction between C-PTSD and depression was significant in the CA1 ({beta}=-0.24, q=0.044). Pairwise comparisons revealed significantly smaller CA1 volumes in individuals with C-PTSD+Depression than controls ({beta}=-0.12, q=0.012), C-PTSD-only ({beta}=-0.17, q=0.001), and Depression-only ({beta}=-0.18, q=0.023). Follow-up analyses revealed sex effects in the hippocampal tail of depressed females, and an interaction effect of C-PTSD and depression in the fimbria of males.\n\nConclusionsCollectively our results suggest that depression is a stronger predictor of hippocampal volumetry than PTSD, particularly in the CA1, and provide compelling evidence of more pronounced hippocampal phenotypes in comorbid PTSD and depression compared to either condition alone.

neuroscience↗

bioRxiv2019

Altered White Matter Microstructural Organization in Post-Traumatic Stress Disorder across 3,049 Adults: Results from the PGC-ENIGMA PTSD Consortium

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed, which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3,049 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1,446 individuals with PTSD and 1,603 controls (2152 males/897 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohens d=-0.12, p=0.0021). The tapetum connects the left and right hippocampus, structures for which structure and function have been consistently implicated in PTSD. Results remained significant/similar after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

neuroscience↗

bioRxiv2018

Adaptive Identification of Cortical and Subcortical Imaging Markers of Early Life Stress and Posttraumatic Stress Disorder

Background and PurposePosttraumatic stress disorder (PTSD) is a heterogeneous condition associated with a wide range of brain imaging abnormalities. Early life stress (ELS) contributes to this heterogeneity, but we do not know how a history of ELS influences traditionally defined brain signatures of PTSD. Here we used a data-driven method to identify shared and unique neuroimaging markers of ELS and PTSD in 97 military veterans. We hypothesized that clustering standard regions of interest would improve classification accuracy of PTSD and ELS, relative to using individual atlas-defined brain regions, with moderate overlap in the patterns associated with each condition.\n\nMethodsWe used a novel machine learning method - evolving partitions to improve classification (EPIC) - to determine how combinations of cortical thickness, surface area, and subcortical brain volumes, could contribute to classification of veterans with PTSD (n=40) relative to trauma-exposed controls (n=57), and classification of ELS within the PTSD (ELS+ n=16; ELS- n=24) and control groups (ELS+ n=16; ELS- n=41). Additional inputs included intracranial volume, age, sex, and self-reported depression.\n\nResultsEPIC improved classification of PTSD, with 71% accuracy, on average. Within groups, EPIC classified ELS with 70% accuracy in controls on average, and 67% accuracy in PTSD; accuracy ranged from 75-84% for the best run of each analysis. For each binary analysis, EPIC identified unique predictors and combinations of neuroimaging variables that contributed to improve group classification from the classifier that modeled input features individually. Self-reported depression was a stronger predictor of PTSD and ELS than any combination of neuroimaging variables, along with adult trauma exposure in controls. Temporoparietal metrics were the strongest neuroimaging predictors of PTSD after depression, whereas regions of the cingulate cortex were strong markers of ELS in both subgroups.\n\nConclusionsCombinatorial machine learning methods such as EPIC may boost power to delineate underlying structural signatures of stress-related neuropathology.

neuroscience↗

bioRxiv2018

Altered cortical brain structure and increased risk for disease seen decades after perinatal exposure to maternal smoking: A study of 9,000 adults in the UK Biobank

Secondhand smoke exposure is a major public health risk that is especially harmful to the developing brain, but it is unclear if early exposure affects brain structure during middle age and older adulthood. Here we analyzed brain MRI data from the UK Biobank in a population-based sample of individuals (ages 44-80) who were exposed (n=2,510) or unexposed (n=6,079) to smoking around birth. We used robust statistical models, including quantile regressions, to test the effect of perinatal smoke exposure (PSE) on cortical surface area (SA), thickness, and subcortical volume. We hypothesized that PSE would be associated with cortical disruption in primary sensory areas compared to unexposed (PSE-) adults. After adjusting for multiple comparisons, SA was significantly lower in the pericalcarine (PCAL), inferior parietal (IPL), and regions of the temporal and frontal cortex of PSE+ adults; these abnormalities were associated with increased risk for several diseases, including circulatory and endocrine conditions. Sensitivity analyses conducted in a hold-out group of healthy participants (exposed, n=109, unexposed, n=315) replicated the effect of PSE on SA in the PCAL and IPL. Collectively our results show a negative, long term effect of PSE on sensory cortices that may increase risk for disease later in life.

neuroscience↗