569 research outputs found

    Beyond the Global Brain Differences:Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers

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    BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and globalbrain differences compared with noncarriers. However, interpreting regional differences is challenging if a globaldifference drives the regional brain differences. Intraindividual variability measures can be used to test for regionaldifferences beyond global differences in brain structure.METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n =30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matchednoncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual’sregional difference and global difference, were used to test for regional differences that diverge from the globaldifference.RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differedmore than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thicknessin regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal andsomatosensory cortex differed more than the global difference in cortical thickness.CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distaland 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distaland 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanismsinvolved in altered neurodevelopment

    Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

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    The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders

    Novel genetic loci associated with hippocampal volume

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    The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

    Novel genetic loci underlying human intracranial volume identified through genome-wide association

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    Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth

    The genetic architecture of the human cerebral cortex

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    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

    Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

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    A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe

    Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

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    Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a ZZ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 <pT<100< p_{\textrm{T}} < 100 GeV and in the pseudorapidity range 2.5<η<42.5 < \eta < 4. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb1^{-1}. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

    Study of the BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

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    The decay BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} is studied in proton-proton collisions at a center-of-mass energy of s=13\sqrt{s}=13 TeV using data corresponding to an integrated luminosity of 5 fb1\mathrm{fb}^{-1} collected by the LHCb experiment. In the Λc+K\Lambda_{c}^+ K^{-} system, the Ξc(2930)0\Xi_{c}(2930)^{0} state observed at the BaBar and Belle experiments is resolved into two narrower states, Ξc(2923)0\Xi_{c}(2923)^{0} and Ξc(2939)0\Xi_{c}(2939)^{0}, whose masses and widths are measured to be m(Ξc(2923)0)=2924.5±0.4±1.1MeV,m(Ξc(2939)0)=2938.5±0.9±2.3MeV,Γ(Ξc(2923)0)=0004.8±0.9±1.5MeV,Γ(Ξc(2939)0)=0011.0±1.9±7.5MeV, m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV}, where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt Λc+K\Lambda_{c}^{+} K^{-} sample. Evidence of a new Ξc(2880)0\Xi_{c}(2880)^{0} state is found with a local significance of 3.8σ3.8\,\sigma, whose mass and width are measured to be 2881.8±3.1±8.5MeV2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV} and 12.4±5.3±5.8MeV12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}, respectively. In addition, evidence of a new decay mode Ξc(2790)0Λc+K\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-} is found with a significance of 3.7σ3.7\,\sigma. The relative branching fraction of BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} with respect to the BD+DKB^{-} \to D^{+} D^{-} K^{-} decay is measured to be 2.36±0.11±0.22±0.252.36 \pm 0.11 \pm 0.22 \pm 0.25, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

    The genetic architecture of the human cerebral cortex

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    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder
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