memVar: an integrated resource for interpreting human membrane protein variation in molecular and disease contexts

Interpreting membrane protein variation requires connecting clinical evidence to the membrane environments and molecular interactions that govern protein functions. Here, we introduce memVar (https://memvar.sunnylab.org), an integrated database of 10,906,688unique single-nucleotide variants from ClinVar, COSMIC, and gnomAD across 7,732 human membrane-associated proteins. memVar reconciles genomic, transcript, and protein coordinates to link variants with membrane topology, bilayer depth, lipid contacts, functional sites, partner-specific interaction interfaces, and variant-effect predictions, alongside disease, tissue-expression and regulatory annotations. Coordinated sequence, structure and variant views retain source provenance and distinguish clinical assertions, experimental observations, and computational predictions. Our analysis reveals that pathogenic/likely pathogenic missense substitutions are enriched in transmembrane segments and predicted protein-protein interaction sites relative to benign/likely benign substitutions, with pooled odds ratios of 2.47 and 6.67, respectively. IntAct-derived interaction loss or decrease was experimentally recorded for 57.9% of pathogenic/likely pathogenic substitutions versus 7.4% of benign/likely benign substitutions. CFTR examples contextualize the established G551D gating defect and prioritize W202R, a variant of uncertain significance, for tests of protein maturation, surface abundance and channel activity. By connecting variant records to specific molecular questions, memVar potentially supports mechanism-oriented investigation and prioritization of functional experiments.

Authors

Institutions

Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-11-05
DOI
https://doi.org/10.64898/2026.11.04.764121
Primary Topic
Genomics and Rare Diseases
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
preprint

memVar: an integrated resource for interpreting human membrane protein variation in molecular and disease contexts

Jianfeng Sun, Yizhou Xu, Siming Huang, Jingyao Zhao
bioRxiv (Cold Spring Harbor Laboratory)
Genomics and Rare Diseases
preprint

memVar: an integrated resource for interpreting human membrane protein variation in molecular and disease contexts

Jianfeng Sun, Yizhou Xu, Siming Huang, Jingyao Zhao
preprint en

Abstract

Interpreting membrane protein variation requires connecting clinical evidence to the membrane environments and molecular interactions that govern protein functions. Here, we introduce memVar (https://memvar.sunnylab.org), an integrated database of 10,906,688unique single-nucleotide variants from ClinVar, COSMIC, and gnomAD across 7,732 human membrane-associated proteins. memVar reconciles genomic, transcript, and protein coordinates to link variants with membrane topology, bilayer depth, lipid contacts, functional sites, partner-specific interaction interfaces, and variant-effect predictions, alongside disease, tissue-expression and regulatory annotations. Coordinated sequence, structure and variant views retain source provenance and distinguish clinical assertions, experimental observations, and computational predictions. Our analysis reveals that pathogenic/likely pathogenic missense substitutions are enriched in transmembrane segments and predicted protein-protein interaction sites relative to benign/likely benign substitutions, with pooled odds ratios of 2.47 and 6.67, respectively. IntAct-derived interaction loss or decrease was experimentally recorded for 57.9% of pathogenic/likely pathogenic substitutions versus 7.4% of benign/likely benign substitutions. CFTR examples contextualize the established G551D gating defect and prioritize W202R, a variant of uncertain significance, for tests of protein maturation, surface abundance and channel activity. By connecting variant records to specific molecular questions, memVar potentially supports mechanism-oriented investigation and prioritization of functional experiments.

bioRxiv (Cold Spring Harbor Laboratory)
Sun Yat-sen University (CN), Hong Kong University of Science and Technology (HK), The Hong Kong University of Science and Technology (Guangzhou) (CN), University of Hong Kong (HK)
Genomics and Rare Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon