André Franke

The paper uses genome-scale metabolic models to predict how diet and lifestyle affect microbial interactions in the gut microbiome, finding shifts from collaboration to competition with high sugar intake.

This study identifies 619 IBD risk signals, resolves 81 high-confidence variants, and prioritizes 664 candidate effector genes using GWAS, eQTL, and exome sequencing.

This study uses exome and genome sequencing to identify 68 genes directly associated with inflammatory bowel disease, providing clearer genetic insights and therapeutic targets.

This study profiles the B cell repertoire in treatment-naive Crohn's disease patients and controls, finding reduced diversity, increased clonality, and altered immunoglobulin clonotype expansions.

This study maps immune responses to fungal antigens in IBD using T cell repertoire sequencing and PhIP-Seq, identifying T cell clonotypes and antibody responses against S. cerevisiae proteins.

The paper uses statistical learning to decode T cell receptor associations with HLA alleles using a large dataset, identifying clonotypes linked to specific HLA alleles and infections.

This study identifies genetic risk factors associated with severe psoriasis and shows that polygenic risk scores can predict severe disease outcomes better than traditional risk factors.

The paper introduces SANSARA, a method for splicing-aware scRNA-Seq analysis, revealing splicing heterogeneity in T cell subsets and interactions between transcription factors.

This study identifies potential biomarkers for IBD diagnosis and monitoring through metaproteomics meta-analysis of over 600 samples.

The paper analyzes over 800,000 human genomes to assess penetrance of clinically relevant variants, finding that 95% of pLoF variants in severe diseases have explanations for lack of disease manifestation.

This study identifies HLA-associated CDR3-QTLs that influence T-cell receptor composition in IBD and healthy controls, revealing disease-specific and universal effects on TRB repertoires.

This study examines how gut bacteria genomes adapt to industrialization, finding convergent genomic responses in stress response, cell envelope remodeling, and central metabolism across different populations.

The paper investigates how industrialization affects microbial and physiological traits in the human gut across diverse populations, finding homogenized microbiomes, reduced diversity, and impaired disease prediction accuracy in less industrialized groups.

This study compares trio, singleton, and standard genome sequencing in rare disease diagnosis, finding trio sequencing has the highest diagnostic yield.

This study evaluates how methodological choices in bulk TCR-Seq affect T cell repertoire profiling, finding that RNA/DNA quality significantly impacts results and that low quantities can be partially compensated by increasing PCR cycles.

The paper identifies and validates T cell receptor clonotypes associated with Crohn's disease and ulcerative colitis, suggesting they are potential therapeutic targets.

This study uses exome sequencing to identify genetic variants in dystonia patients, finding 137 likely pathogenic variants in 51 genes and expanding the known phenotypic spectrum of dystonia-related genes.

The paper identifies public TCRB sequences expanded in CD or UC, associated with HLA alleles and antigen-specific immune responses, showing differential expansion in CD compared to UC and healthy controls.

This study performs a GWAS meta-analysis of psoriasis, identifying 109 susceptibility loci, including 45 new ones, and highlights potential therapeutic targets and disease mechanisms.

The paper develops an improved polygenic score for idiopathic Parkinson's disease, showing higher discriminative performance and explaining variable penetrance in genetic forms of the disease.

The paper develops a multivariate methylation risk score using blood DNA methylation data to predict dementia risk and cognitive impairment in Alzheimer's and Parkinson's disease cohorts.

The paper introduces a method to compress genetic data using autoencoders that leverage linkage disequilibrium structure, achieving high reconstruction accuracy while reducing data size.

Seq2MAIT identifies MAIT cells from bulk TCR-sequencing data using a transformer-based model, achieving AUROC >0.80 across datasets.

The paper uses metabolic modeling to predict precision prebiotics that specifically enhance the abundance of a beneficial microbiome species in C. elegans.

The paper maps DNA methylation quantitative trait loci (meQTL) in three tissues and uses Mendelian randomization to link DNAm to Alzheimer's and Parkinson's disease risk.

Rare-variant depletion in 1kb windows of 76,156 gnomAD genomes, versus feature-adjusted mutation expectations, marks regulatory elements and outperforms seven alternative scores at flagging functional non-coding variants.

The paper develops a method to infer compound heterozygosity from exome sequencing data, achieving high accuracy in phasing rare variants for recessive disease diagnosis.

This study identifies four novel DNA methylation loci in the entorhinal cortex associated with Alzheimer's disease and finds significant epigenetic age acceleration in patients.

Pathonoia detects viruses and bacteria in RNA-seq data with high precision and recall, outperforming existing methods and providing insights into microbe-host interactions.