Michael H Preuss

This paper decomposes the genetic architecture of schizophrenia and bipolar disorder into shared and disorder-specific components, revealing distinct biological pathways and associations with intermediate traits.

The paper develops a scalable framework to generate harmonized mtDNA datasets from existing sequencing data across biobanks, enabling population-scale mitochondrial genomics without new sequencing.

This paper identifies genetic loci associated with schizophrenia and bipolar disorder using cognitive pleiotropy, revealing shared and disorder-specific biological mechanisms.

The paper introduces DIMPLE-GWAS, a dimensionality reduction framework for GWAS of brain scans, identifying 25 latent phenotypes with higher heritability and discovering 104 new significant loci.

This study identifies genetic subtypes of obesity that uncouple adiposity from cardiometabolic risks, revealing distinct biological pathways and protein associations.

This study identifies novel genetic signals associated with severe obesity through GWAS and shows strong genetic overlap with BMI, highlighting shared comorbidities and lifestyle interactions.

This study identifies 31 plasma proteins and expands genetic loci associated with PCOS, highlighting metabolic and hormonal influences and polygenic risk effects on cardio-metabolic outcomes.

The paper identifies 83 rare lncRNA variant sets associated with blood lipid levels using WGS data from the TOPMed program and validates some in UK Biobank data.

BridgePRS improves polygenic risk score accuracy in non-European populations by leveraging shared genetic effects across ancestries, outperforming existing methods in simulated and real data.

The paper presents a comprehensive catalog of structural variants across 138,134 individuals, identifying novel variants and their associations with cardio-metabolic and hematologic traits.

This study evaluates polygenic risk score methods across diverse biobanks and ancestries, finding that European reference panels often yield better performance, while PRS-CS outperforms P+T for high-heritability traits.

This study uses whole-genome sequencing to analyze mosaic chromosomal alterations across diverse ancestries, finding higher rates in certain populations and associations with germline variants.

This paper shows that meta-analysis fine-mapping is often miscalibrated due to cohort heterogeneity and introduces a QC method to identify suspicious loci.

The paper performs whole genome sequence analysis of plasma lipid levels in 66,329 individuals, identifying new lipid-associated alleles, including rare non-coding variants.

Meta-analysis of harmonized GWAS from up to 18 biobanks (six ancestry groups) across 14 endpoints replicated 320 known loci and identified 188 apparently novel loci.

This paper conducts a multi-ancestry GWAS of major depression, identifying 190 loci and 354 genes, with findings showing increased fine-mapping power and bidirectional BMI relationship in European ancestry samples.

The paper uses bidirectional Mendelian randomization to show LTL lengthening increases CHIP risk, while CHIP accelerates LTL shortening, with modest mediation between CHIP and CAD via LTL.

This study identifies novel genetic loci for BMI, height, and WHRadjBMI in Hispanic/Latino populations and shows the benefits of ancestral diversity in GWAS.

The paper estimates heritability for height and BMI using whole-genome sequence data and finds that rare variants contribute significantly to the missing heritability.

This study identifies 277 T2D loci using diverse populations and improves fine-mapping to assess causal genes and mechanisms, enhancing clinical translation.

This study evaluates the prognostic value of polygenic risk scores for schizophrenia and finds they do not improve outcome prediction beyond clinical features.

The paper identifies novel genetic associations for biomarker traits in non-European UK Biobank populations, highlighting missed signals in European-centric analyses.

The paper evaluates penetrance and variable expressivity of monogenic metabolic conditions using exome data from 77,184 individuals, finding that monogenic variants have larger effect sizes than polygenic scores but low penetrance.

This paper performs a large-scale TWAS of blood cell phenotypes, identifies 239 gene-trait associations, and develops an R Shiny app to visualize TWAS results.

This study identifies 5,552 blood-cell trait-variant associations across 746,667 individuals from 5 global populations, including 71 novel loci and ancestry-specific variants not found in European ancestry populations.

This study identifies 5,106 new genetic variants associated with blood cell traits using large-scale GWAS, highlighting the polygenic and monogenic basis of hematopoiesis.

This study identifies 242 genetic loci for glycaemic traits using trans-ancestry meta-analysis, finding 99 novel loci and improved fine-mapping resolution compared to single-ancestry analyses.

This study identifies 210 genetic loci associated with the PR interval through multi-ancestry GWAS, highlighting their role in cardiac conduction and cardiovascular disease.