André Altmann

Incorporating Multi-threshold Polygenic Risk in Hippocampal-based Normative Models Improves Cognitive Decline Prediction

The paper improves cognitive decline prediction by integrating multi-threshold polygenic scores into hippocampal-based normative models using UK Biobank data.

Normative models reveal distinct cortical abnormalities to dimensions of psychopathologies in preadolescents

The paper identifies cortical abnormalities linked to psychopathological dimensions in preadolescents using normative models and latent class analysis.

Tau-first subtype of Alzheimer's disease consistently identified across in vivo and post mortem studies

The paper identifies a tau-first subtype of Alzheimer's disease through analysis of post mortem and in vivo data, showing higher soluble TREM2 levels in tau-first cases.

Fed-ComBat: A Generalized Federated Framework for Batch Effect Harmonization in Collaborative Studies

Fed-ComBat harmonizes batch effects in decentralized data, showing comparable results to centralized methods for linear and nonlinear cases.

Polygenic coronary artery disease association with brain atrophy in the cognitively impaired

This study examines the association between polygenic risk scores for coronary artery disease and brain atrophy in cognitively impaired individuals, finding CAD PRS more predictive of brain atrophy in some groups.

Nomograms of Human Hippocampal Volume Shifted by Polygenic Scores

The paper builds genetically adjusted hippocampal volume nomograms using polygenic scores and evaluates their clinical impact in detecting dementia patients.

Dynamic trajectories of connectome state transitions are heritable

The paper identifies heritable dynamic features of brain connectome states and links them to cognitive performance using resting-state fMRI.

pySuStaIn: a Python implementation of the Subtype and Stage Inference algorithm

pySuStaIn provides a Python implementation of the SuStaIn algorithm to infer disease subtypes and stages from cross-sectional data.

Multi view based imaging genetics analysis on Parkinson disease

The paper proposes a multi-view workflow for integrating imaging and genetic data in Parkinson's Disease to identify potential genetic biomarkers.

A systems-level analysis highlights microglial activation as a modifying factor in common forms of human epilepsy

The paper identifies microglial activation as a factor contributing to cortical thinning in epilepsy by integrating neuroimaging and gene expression data.

Network propagation of rare mutations in Alzheimer’s disease reveals tissue-specific hub genes and communities

The paper introduces NETPAGE, a network propagation method to analyze rare mutations in Alzheimer's disease, identifying tissue-specific hub genes and predicting disease status.

Genetic variation in CSMD1 affects amygdala connectivity and prosocial behavior

This study identifies a genetic variant in CSMD1 associated with amygdala connectivity and prosocial behavior through a GWAS of brain networks in adolescents.

White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA Epilepsy study

This study identifies white matter microstructural differences across epilepsy syndromes using diffusion MRI data from a large multicenter cohort.

Analysis of brain atrophy and local gene expression in genetic frontotemporal dementia

The paper investigates the relationship between gene expression and brain atrophy in genetic frontotemporal dementia, finding correlations between atrophy patterns and specific gene sets related to vascular, glial, and neuronal functions.

Longitudinal prediction of outcome in idiopathic pulmonary fibrosis using automated CT analysis

This study evaluates computer-derived CT variables (CALIPER vessel-related structures) as predictors of outcome in IPF, finding they outperform FVC decline in predicting prognosis and increasing trial power when used as co-endpoints.

Modeling longitudinal imaging biomarkers with parametric Bayesian multi-task learning

This paper introduces a Bayesian multi-task learning model for longitudinal imaging biomarkers, showing improved trajectory inference and disease effect detection in Alzheimer's disease data.

Evidence for bias of genetic ancestry in resting state functional MRI

This study shows genetic ancestry can be predicted from resting state fMRI data, indicating ancestry influences functional connectivity patterns.

Grey matter biomarker identification in Schizophrenia: detecting regional alterations and their underlying substrates

This paper develops a machine learning framework to identify sparse grey matter biomarkers in Schizophrenia and their biological substrates using structural MRI data.

Distance Is Not Everything In Imaging Genomics Of Functional Networks: Reply To A Commentary On Correlated Gene Expression Supports Synchronous Activity In Brain Networks

The paper responds to a commentary challenging its 2015 findings that gene expression similarity within functional brain networks is higher than expected by chance, and defends the original results.