Shicheng Guo
Human Genetics · Global Collaborations

Consortium

The international consortia turning population-scale human genetics into biology, targets, and medicines.


Modern human genetics is a team sport. No single cohort is large enough to resolve rare-variant effects or rare diseases, so the field organizes into consortia — harmonizing phenotypes, sharing summary statistics, and meta-analyzing across millions of participants. Below is a curated map of the consortia that matter most for statistical genetics, target identification, and translational drug discovery.

Rare-Variant & Sequencing Consortia

BRaVa

The Biobank Rare Variant Analysis consortium runs harmonized, gene-based rare-variant association tests across global biobanks. Using a shared phenotype dictionary and a common SAIGE-GENE+ pipeline, BRaVa meta-analyzes exome/genome sequencing to find rare coding variants driving disease — the resolution single biobanks lack.

Rare variantsExomeMeta-analysis

gnomAD

The Genome Aggregation Database (successor to ExAC) is the field's reference for allele frequencies, aggregating exomes and genomes from hundreds of thousands of individuals across diverse populations. Essential for variant interpretation, constraint metrics (pLI, LOEUF), and filtering candidate disease variants.

Allele frequencyConstraintBroad

TOPMed

NHLBI's Trans-Omics for Precision Medicine program generates deep whole-genome sequencing across diverse cohorts, powering rare-variant discovery for heart, lung, blood, and sleep traits — and underpinning one of the most widely used imputation reference panels.

WGSNHLBIImputation

Genebass

A browsable resource of gene-based and single-variant association results from UK Biobank exome sequencing (~400k participants, thousands of phenotypes). A practical entry point for exploring exome-wide rare-variant signals without re-running analyses.

UK BiobankExomePheWAS

Regeneron Genetics Center

Through the DiscovEHR collaboration and large-scale exome sequencing of biobank cohorts, the RGC links genetics to electronic health records at industrial scale — a model for genetics-first drug-target discovery in pharma.

ExomeEHRTarget ID

Biobank Networks & Meta-Analysis

GWAS Aggregation, Catalogs & Target ID

Trait- & Disease-Specific Consortia

Psychiatric Genomics Consortium

The PGC is the largest collaboration in the history of psychiatry, meta-analyzing GWAS for schizophrenia, bipolar disorder, depression, ADHD, autism, and more — a template for how to scale genetics in complex, heterogeneous traits.

PsychiatryGWASMeta-analysis

GIANT

The Genetic Investigation of ANthropometric Traits consortium defined the genetic architecture of height, BMI, and body shape across millions of individuals — landmark work on polygenicity and effect-size distributions.

AnthropometricHeight/BMIPolygenic

CHARGE

Cohorts for Heart and Aging Research in Genomic Epidemiology unites prospective cohorts to study cardiovascular, metabolic, and aging-related phenotypes, pioneering large-scale GWAS meta-analysis design.

CardiovascularAgingCohorts

ENIGMA

Enhancing NeuroImaging Genetics through Meta-Analysis links brain imaging phenotypes to genetics across hundreds of institutions, mapping the genetic basis of brain structure and neuropsychiatric disease.

NeuroimagingBrainGenetics

DIAGRAM / DIAMANTE

The diabetes genetics consortia (DIAGRAM and its trans-ancestry successor DIAMANTE) have driven type 2 diabetes locus discovery and fine-mapping across global populations, a model for ancestry-diverse GWAS.

Type 2 diabetesFine-mappingTrans-ancestry

Global Lipids Genetics Consortium

The GLGC meta-analyzes blood-lipid GWAS (LDL, HDL, triglycerides, total cholesterol) across millions of participants — work that has directly informed cardiovascular drug targets such as PCSK9.

LipidsCardiovascularPCSK9

CKDGen

The Chronic Kidney Disease Genetics consortium meta-analyzes GWAS for kidney function (eGFR), CKD, and related biomarkers across global cohorts, mapping the genetic architecture of renal disease.

KidneyeGFRGWAS

Functional Genomics & Reference Resources

This is a curated, non-exhaustive guide focused on consortia most relevant to statistical genetics and translational drug discovery. Membership, scale, and scope evolve continually — follow each consortium's site for current data releases and participation details.