Biology subjects

Lund, M. J.

Publications and source records attributed to Lund, M. J..

4 recordsLinked to original sources

bioRxiv2018

Genetic control of variability in subcortical and intracranial volumes

Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in nine key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n=25,575 individuals; 8 to 89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in cortical thickness, thalamus, pallidum, and intracranial volumes. The variance-controlling loci included genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.

neuroscience↗

bioRxiv2018

The dark side of the mean: brain structural heterogeneity in schizophrenia and its polygenic risk.

ImportanceBetween-subject variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients. However, such group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature\n\nObjectiveTo compare brain structural variability between individuals with SZ and healthy controls (HC) and to test if respective variability reflects the polygenic risk for SZ (PRS) in HC.\n\nDesign, Setting, and ParticipantsWe compared MRI derived cortical thickness and subcortical volumes between 2,010 healthy controls and 1,151 patients with SZ across 16 cohorts. Secondly, we tested for associations between PRS and MRI features in 12,490 participants from UK Biobank.\n\nMain Outcomes and MeasuresWe modeled mean and dispersion effects of SZ and PRS using double generalized linear models. We performed vertex-wise analyses for thickness, and region-of-interest analysis for cortical, subcortical and hippocampal subfield volumes. Follow-up analyses included within-sample analysis, controlling for intracranial volume and population covariates, test of robustness of PRS threshold, and outlier removal.\n\nResultsCompared to controls, patients with SZ showed higher heterogeneity in cortical thickness, cortical and ventricle volumes, and hippocampal subfields. Higher PRS was associated with thinner frontal and temporal cortices, as well as smaller left CA2/3, but was not significantly associated with dispersion.\n\nConclusion and relevanceSZ is associated with substantial brain structural heterogeneity beyond the mean differences. These findings possibly reflect higher differential sensitivity to environmental and genetic perturbations in patients, supporting the heterogeneous nature of SZ. Higher PRS for SZ was associated with thinner fronto-temporal cortices and smaller subcortical volumes, but there were no significant associations with the heterogeneity in these measures, i.e. the variability among individuals with high PRS were comparable to the variability among individuals with low PRS. This suggests that brain variability in SZ results from interactions between environmental and genetic factors that are not captured by the PGR. Factors contributing to heterogeneity in fronto-temporal cortices and hippocampus are thus key to further our understanding of how genetic and environmental factors shape brain biology in SZ.\n\nKey PointsQuestion: Is schizophrenia and its polygenic risk associated with brain structural heterogeneity in addition to mean changes?\n\nFindings: In a sample of 1151 patients and 2010 controls, schizophrenia was associated with increased heterogeneity in fronto-temporal thickness, cortical, ventricle, and hippocampal volumes, besides robust reductions in mean estimates. In an independent sample of 12,490 controls, polygenic risk for schizophrenia was associated with thinner fronto-temporal cortices and smaller CA2/3 of the left hippocampus, but not with heterogeneity.\n\nMeaning: Schizophrenia is associated with increased inter-individual differences in brainstructure, possibly reflecting clinical heterogeneity, gene-environment interactions, or secondary disease factors.

neuroscience↗

bioRxiv2018

Narcolepsy type 1 patients have abnormal brain activation to neutral-rated movies in humor-paradigm

Narcolepsy type 1 is a neurological sleep disorder mainly characterized by excessive daytime sleepiness, fragmented night sleep, and cataplexy (muscle atonia triggered by emotions). To characterize brain activation patterns in response to neutral-rated and fun-rated movies in narcolepsy type 1 we performed functional magnetic resonance imaging during a paradigm consisting of 30 short movies (25/30 with a humorous punchline; 5/30 without a humorous punchline (but with similar build-up/anticipation)) that the participants rated based on their humor experience. We included 41 narcolepsy type 1 patients (31 females, mean age 23.6 years, 38/41 H1N1-vaccinated, 41/41 HLA-DQB1*06:02-positive, 40/40 hypocretin-deficient) and 44 first-degree relatives (24 females, mean age 19.6 years, 30/44 H1N1-vaccinated, 27/44 HLA-DQB1*06:02-positive) as controls. Group-level inferences were made using permutation testing.\n\nPermutation testing revealed no significant differences in the average ratings of patients and controls. Functional magnetic resonance imaging analysis revealed that both groups showed higher activations in response to fun-rated movies in several brain regions associated with humor processing, with no significant group differences. In contrast, patients showed significantly higher activation compared to controls during neutral-rated movies; including bilaterally in the thalamus, pallidum, putamen, amygdala, hippocampus, middle temporal gyrus, cerebellum, brainstem and in the left precuneus, supramarginal gyrus and caudate.\n\nThe presence of a humorous punchline in a neutral-rated movie is important since we found no brain overactivation for narcolepsy type 1 patients for movies without a humorous punchline (89.0% neutral-rated) compared with controls.\n\nFurther, a comparison between fun-rated and neutral-rated movies revealed a pattern of higher activation during fun-rated movies in controls, patients showed no significant differentiation between these states. Group analyses revealed significantly stronger differentiation between fun-rated and neutral-rated movies in controls compared with patients, including bilaterally in the inferior frontal gyrus, thalamus, putamen, precentral gyrus, lingual gyrus, supramarginal gyrus, occipital areas, temporal areas, cerebellum and in the right hippocampus, postcentral gyrus, pallidum and insula.\n\nIn conclusion, during neutral-rated movies, narcolepsy type 1 patients showed significantly higher activation in several cortical and subcortical regions previously implicated in humor and REM sleep, including the thalamus and basal ganglia. The relative lack of differentiation between neutral-rated and fun-rated movies in narcolepsy type 1 patients might represent insight into the mechanisms associated with cataplexy, in which a long-lasting hypervigilant state could represent risk (hypersensitivity to potential humorous stimuli) for the narcolepsy type 1 patients, which seem to have a lower threshold for activating the humor response, even during neutral-rated movies.

neuroscience↗

bioRxiv2018

Genetics of brain age suggest an overlap with common brain disorders

Numerous genetic and environmental factors contribute to psychiatric disorders and other brain disorders. Common risk factors likely converge on biological pathways regulating the optimization of brain structure and function across the lifespan. Here, using structural magnetic resonance imaging and machine learning, we estimated the gap between brain age and chronological age in 36,891 individuals aged 3 to 96 years, including individuals with different brain disorders. We show that several disorders are associated with accentuated brain aging, with strongest effects in schizophrenia, multiple sclerosis and dementia, and document differential regional patterns of brain age gaps between disorders. In 16,269 healthy adult individuals, we show that brain age gap is heritable with a polygenic architecture overlapping those observed in common brain disorders. Our results identify brain age gap as a genetically modulated trait that offers a window into shared and distinct mechanisms in different brain disorders.

neuroscience↗