Preference for biological motion is reduced in ASD: implications for clinical trials and the search for biomarkers.

BACKGROUND: The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct research towards fruitful areas for future investigation. Here we focus on perception of biological motion, a promising index of social brain function which may be altered in ASD. In a large sample ranging from childhood to adulthood, we assess whether biological motion preference differs in ASD compared to neurotypical participants (NT), how differences are modulated by age and sex and whether they are associated with dimensional variation in concurrent or later symptomatology. METHODS: Eye-tracking data were collected from 486 6-to-30-year-old autistic (N = 282) and non-autistic control (N = 204) participants whilst they viewed 28 trials pairing biological (BM) and control (non-biological, CTRL) motion. Preference for the biological motion stimulus was calculated as (1) proportion looking time difference (BM-CTRL) and (2) peak look duration difference (BM-CTRL). RESULTS: The ASD group showed a present but weaker preference for biological motion than the NT group. The nature of the control stimulus modulated preference for biological motion in both groups. Biological motion preference did not vary with age, gender, or concurrent or prospective social communicative skill within the ASD group, although a lack of clear preference for either stimulus was associated with higher social-communicative symptoms at baseline. LIMITATIONS: The paired visual preference we used may underestimate preference for a stimulus in younger and lower IQ individuals. Our ASD group had a lower average IQ by approximately seven points. 18% of our sample was not analysed for various technical and behavioural reasons. CONCLUSIONS: Biological motion preference elicits small-to-medium-sized case-control effects, but individual differences do not strongly relate to core social autism associated symptomatology. We interpret this as an autistic difference (as opposed to a deficit) likely manifest in social brain regions. The extent to which this is an innate difference present from birth and central to the autistic phenotype, or the consequence of a life lived with ASD, is unclear

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

BACKGROUND: Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed. METHODS: We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2-32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants' MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%-30% split). RESULTS: In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52-0.62, specificity 0.59-0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset. LIMITATIONS: The statistical power to detect weak effects-of the magnitude of those found in the training dataset-in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset's effects. CONCLUSIONS: This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects

The meaning of significant mean-group differences for biomarker discovery

Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterogeneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between “cases” and “controls,” which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research—autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen’s d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the “on average” when summarising their findings in their abstracts (“autistic people have deficits in X”), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers

Preference for biological motion is reduced in ASD: implications for clinical trials and the search for biomarkers

Background: The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct research towards fruitful areas for future investigation. Here we focus on perception of biological motion, a promising index of social brain function which may be altered in ASD. In a large sample ranging from childhood to adulthood, we assess whether biological motion preference differs in ASD compared to neurotypical participants (NT), how differences are modulated by age and sex and whether they are associated with dimensional variation in concurrent or later symptomatology. Methods: Eye-tracking data were collected from 486 6-to-30-year-old autistic (N = 282) and non-autistic control (N = 204) participants whilst they viewed 28 trials pairing biological (BM) and control (non-biological, CTRL) motion. Preference for the biological motion stimulus was calculated as (1) proportion looking time difference (BM-CTRL) and (2) peak look duration difference (BM-CTRL). Results: The ASD group showed a present but weaker preference for biological motion than the NT group. The nature of the control stimulus modulated preference for biological motion in both groups. Biological motion preference did not vary with age, gender, or concurrent or prospective social communicative skill within the ASD group, although a lack of clear preference for either stimulus was associated with higher social-communicative symptoms at baseline. Limitations: The paired visual preference we used may underestimate preference for a stimulus in younger and lower IQ individuals. Our ASD group had a lower average IQ by approximately seven points. 18% of our sample was not analysed for various technical and behavioural reasons. Conclusions: Biological motion preference elicits small-to-medium-sized case–control effects, but individual differences do not strongly relate to core social autism associated symptomatology. We interpret this as an autistic difference (as opposed to a deficit) likely manifest in social brain regions. The extent to which this is an innate difference present from birth and central to the autistic phenotype, or the consequence of a life lived with ASD, is unclear

Preference for biological motion is reduced in ASD: implications for clinical trials and the search for biomarkers.

BACKGROUND: The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct research towards fruitful areas for future investigation. Here we focus on perception of biological motion, a promising index of social brain function which may be altered in ASD. In a large sample ranging from childhood to adulthood, we assess whether biological motion preference differs in ASD compared to neurotypical participants (NT), how differences are modulated by age and sex and whether they are associated with dimensional variation in concurrent or later symptomatology. METHODS: Eye-tracking data were collected from 486 6-to-30-year-old autistic (N = 282) and non-autistic control (N = 204) participants whilst they viewed 28 trials pairing biological (BM) and control (non-biological, CTRL) motion. Preference for the biological motion stimulus was calculated as (1) proportion looking time difference (BM-CTRL) and (2) peak look duration difference (BM-CTRL). RESULTS: The ASD group showed a present but weaker preference for biological motion than the NT group. The nature of the control stimulus modulated preference for biological motion in both groups. Biological motion preference did not vary with age, gender, or concurrent or prospective social communicative skill within the ASD group, although a lack of clear preference for either stimulus was associated with higher social-communicative symptoms at baseline. LIMITATIONS: The paired visual preference we used may underestimate preference for a stimulus in younger and lower IQ individuals. Our ASD group had a lower average IQ by approximately seven points. 18% of our sample was not analysed for various technical and behavioural reasons. CONCLUSIONS: Biological motion preference elicits small-to-medium-sized case-control effects, but individual differences do not strongly relate to core social autism associated symptomatology. We interpret this as an autistic difference (as opposed to a deficit) likely manifest in social brain regions. The extent to which this is an innate difference present from birth and central to the autistic phenotype, or the consequence of a life lived with ASD, is unclear

VARIATION IN MITOCHONDRIAL-DNA LEVELS IN MUSCLE FROM NORMAL CONTROLS - IS DEPLETION OF MTDNA IN PATIENTS WITH MITOCHONDRIAL MYOPATHY A DISTINCT CLINICAL SYNDROME

Recent studies have identified a group of patients with cytochrome oxidase (COX) deficiency presenting in infancy associated with a deficiency of mtDNA in muscle or other affected tissue (Moraes et al 1991). We used a navel approach to compare the level of mitochondrial (mtDNA) compared to nuclear DNA in skeletal muscle from a group of patients and controls, based on dot blots that were hybridized with a mtDNA probe labelled with S-35[dCTP] and a reference nuclear DNA probe labelled with [P-32]dCTP. The ratio of mtDNA to nuclear DNA varied in samples from different muscles of the same individual. Secondly, fetal muscle had very low levels of mtDNA compared to nuclear DNA, and data from older controls (cross-sectional rather than sequential) suggest that this increases rapidly over the first 3 months after birth and thereafter more slowly. Four patients with COX deficiency had levels of mtDNA that were below the age-specific range defined by 'normal' quadriceps muscle. The clinical features of two of these patients were similar to earlier case reports of mtDNA depletion. Tn three patients the clinical course was relatively benign compared to cases that have previously been described. Levels of mtDNA in skeletal muscle from some patients with other farms of muscle disease were also found to be low, suggesting that mtDNA depletion, possibly related to depletion of mitochondria, may be a relatively non-specific response of muscle to various pathological processes. However, there does appear to be a distinctive group of young patients with reduced cytochrome oxidase activity in muscle, in whom marked mtDNA depletion reflects the primary defect

The N170 face-sensitive brain response: toward a stratification biomarker for ASD

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterised by difficulties in social communication, but also great heterogeneity. To offer individualised medicine approaches, we need to better target interventions by stratifying autistic people into subgroups with different biological profiles and/or prognoses. We sought to validate neural responses to faces as a potential stratification biomarker in ASD by measuring neural (electroencephalography/EEG) responses to faces (critical in social interaction) in N=436 children and adults with and without ASD. The speed of early-stage face processing (N170 latency) was on average slower in ASD than age-matched controls. In addition, N170 latency was associated with responses to faces in the fusiform gyrus during an fMRI task and polygenic scores for ASD, triangulating links to social biology. Critically, within the ASD group N170 latency predicted change in adaptive socialisation skills over an 18-month follow-up period; data-driven clustering identified a subgroup with slower brain responses and poor social prognosis. Use of a distributional data-driven cut-off was associated with predicted improvements of power in simulated clinical trials targeting social functioning. Taken together, this provides converging evidence for the utility of the N170 as a stratification biomarker to identify biologically and prognostically defined subgroups in ASD, and may provide a blueprint for similar endeavours in other psychiatric conditions

Expert survey data on key challenges, drivers, and ecosystem services across mountains worldwide

Data are survey responses collected between 2014-2016 from experts working in 57 different mountain systems around the world, assessing threats to mountain social-ecological systems (MtSES) and the cross-scale ecosystem services MtSES provide.Mountain social-ecological systems (MtSES) are vital to humanity, providing ecosystem services to over half the planet's human population. Despite their importance, there has been no global assessment of threats to MtSES, even as they face unprecedented challenges to their sustainability. With survey data from 57 MtSES sites worldwide, we test a conceptual model of the types and scales of stressors and ecosystem services in MtSES and explore their distinct configurations according to their primary economic orientation and land use. We find that MtSES worldwide are experiencing both gradual and abrupt climatic, economic, and governance changes, with policies made by outsiders as the most ubiquitous challenge. Mountains that support primarily subsistence-oriented livelihoods, especially agro-pastoral systems, deliver abundant services but are also most at risk. Moreover, transitions from subsistence- to market-oriented economies are often accompanied by increased physical connectedness, reduced diversity of cross-scale ecosystem services, lowered importance of local knowledge, and shifting vulnerabilities to threats. Addressing the complex challenges facing MtSES and catalyzing transformations to MtSES sustainability will require cross-scale partnerships among researchers, stakeholders and decision-makers to jointly identify desired futures and adaptation pathways, assess tradeoffs in prioritizing ecosystem services, and share best practices for sustainability. These transdisciplinary approaches will allow local stakeholders, researchers and practitioners to jointly address MtSES knowledge gaps while simultaneously focusing on critical issues of poverty and food security.Ideas presented in this paper were first developed at a workshop supported by the Mountain Research Initiative (MRI), the Colorado State University (CSU) Warner College of Natural Resources, and the CSU Office of International Programs. Further support was provided by the National Science Foundation, NSF #DEB 1414106. RM was supported under the Climate Change Impacts on Ecosystem Services and Food Security in Eastern Africa (CHIESA) funded by the Ministry of Foreign Affairs of Finland