Analysis of 173,303 exomes and genomes in the Pakistan Genome Resource

Naturally occurring loss-of-function variants in human genes enable drug target discovery because they mimic pharmacological inhibition of proteins. However, the study of these genetic variants is constrained by their rarity. Sequencing of diverse populations, particularly those enriched in familial relatedness, has been postulated to promote discovery of rare genetic variants1–3. Here we present the Pakistan Genome Resource, a South Asian biobank with high familial relatedness comprising 173,303 participants, who collectively carry naturally occurring homozygous loss-of-function variants in 6,476 genes. We describe the genetic architecture of this population, associations between genes and biomarkers, the distribution of loss-of-function variants across molecular pathways, and recall-by-genotype studies of therapeutically relevant genes. The Pakistan Genome Resource expands the catalogue of human genetic variants, provides a comprehensive genetic reference resource for the Pakistani population, and demonstrates the value of studying diverse cohorts to advance human health. The Pakistan Genome Resource compiles biobank data from 173,303 individuals with high familial relatedness, broadening the catalogue of human genetic variation and establishing a population-specific genomic reference for Pakistan.

Authors

Institutions

Publication Details

Journal
Nature
Published
2026-06-17
DOI
https://doi.org/10.1038/s41586-026-10667-5
Citations
1
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
11.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of 173,303 exomes and genomes in the Pakistan Genome Resource

Makoto Asaumi, M Asif Khan, Caitlin Forsythe, Aflak Rasheed et al.
1 citations
Nature
Genomics and Rare Diseases
11.42
article

Analysis of 173,303 exomes and genomes in the Pakistan Genome Resource

Makoto Asaumi, M Asif Khan, Caitlin Forsythe, Aflak Rasheed, Jason Portnoy, Nazish Butt, M. Shahid Mukhtar, Luca Lotta, Muhammad Ali, Syed Asif Raza Zaidi, Shahzad Ali Khan, John D. Overton, Laura M. Cremona, Chihiro Hata, Muhammad Rehan Mian, Roshina Anjum, Muhammad Noor Wazir, Christina Beechert, Riffat Sultana, Ambreen Muddassir, Shruthi Bandyadka, Katherine R. Smith, C Willer, Stewart MacArthur, Muhammad Jahanzaib, Faizan Aslam, Muhammad Sadik Memon, Anjum Jalal, Ikuyo Kou, Daniel P. Denning, Jeffrey G. Reid, Christopher Koch, Kristy Guevara, Adil Mahmood, Muhammad Tahir Bashir, Maya Ghoussaini, Marcus B. Jones, Asadullah Khan, Michael Lattari, Rahmat Ghaffar, Mateen Akram, Sebastian Wasilewski, Muhammad Usman Musharraf, Mona Nafde, Wataru Morii, Maleeha Khan, Alison Fenney, Muhammad Bilal, Slavé Petrovski, Shahid Abbas, Shareef Khalid, Manuel Allen Revez Ferreira, Alexander Lopez, Katherine Siminovitch, Andrew Deubler, Jonathan Marchini, Kia Manoochehri, Brian Doyon, S Khan, Hang Du, Eugene Kalyuskin, Tariq Mehmood, Marium Dahar, Namra Saqib, Khalid Parvez Babar, Abdul Lateef Rodeni, Tahir Rasool, Wafa Gul, Lyndon Mitnaul, Alan Shuldiner, Lourdes Crane, Aris Baras, Adolfo Ferrando, William Salerno, Muhammad Hussain, Sanaullah Jan, Ali Hyder, Kieren Lythgow, Sequencing and Lab Operations, Zhenhua Gu, Umar Usman, Kousik Kundu, Rehan Abdullah, Aneeqa Bano, Samreen Bugti, Musfireh Siddiqeh, Javed Iqbal, Muhammad Bilal Liaqat, RGC Management and Leadership Team, Muhammad Akram Bajwa, Mohsin Iqbal Haroon, Muhammad Haroon, Irfan Majeed, Nauman Hashmani, Gonçalo Abecasis, Saima Naz Mohsin, Erin Fuller, Giovanni Coppola, Noor Ul Hadi, Lubna Kamani
article en
1 citations

Abstract

Naturally occurring loss-of-function variants in human genes enable drug target discovery because they mimic pharmacological inhibition of proteins. However, the study of these genetic variants is constrained by their rarity. Sequencing of diverse populations, particularly those enriched in familial relatedness, has been postulated to promote discovery of rare genetic variants1–3. Here we present the Pakistan Genome Resource, a South Asian biobank with high familial relatedness comprising 173,303 participants, who collectively carry naturally occurring homozygous loss-of-function variants in 6,476 genes. We describe the genetic architecture of this population, associations between genes and biomarkers, the distribution of loss-of-function variants across molecular pathways, and recall-by-genotype studies of therapeutically relevant genes. The Pakistan Genome Resource expands the catalogue of human genetic variants, provides a comprehensive genetic reference resource for the Pakistani population, and demonstrates the value of studying diverse cohorts to advance human health. The Pakistan Genome Resource compiles biobank data from 173,303 individuals with high familial relatedness, broadening the catalogue of human genetic variation and establishing a population-specific genomic reference for Pakistan.

Nature
AstraZeneca (United Kingdom) (GB), Services Institute of Medical Sciences (PK), Novartis (Switzerland) (CH), Jinnah Postgraduate Medical Center (PK), Liaquat University of Medical & Health Sciences (PK), Astellas Pharma (Japan) (JP), Punjab Institute of Cardiology (PK), Rawalpindi Medical University (PK), Regeneron (United States) (US), Allama Iqbal Medical College (PK), Punjab Medical College (PK), Liaquat National Hospital (PK), CMH Lahore Medical College and Institute of Dentistry (PK), Columbia University Irving Medical Center (US), Pakistan Army (PK), Lahore General Hospital (PK), Bolan University of Medical and Health Sciences (PK), Hayatabad Medical Complex (PK), Shaikh Zayed Hospital (PK), Karachi Institute of Heart Diseases (PK), Allied Hospital (PK), Bahawal Victoria Hospital (PK), University of Health Sciences Lahore (PK), Shaheed Mohtarma Benazir Bhutto Medical University (PK), Novartis (China) (CN), Ghazi University (PK), AstraZeneca (Poland) (PL), Asian Institute of Gastroenterology (IN), University of Faisalabad (PK), Center for Non-Communicable Diseases (PK), Shaikh Zayed Postgraduate Medical Institute (PK), Health Services Academy (PK)
Good health and well-being
Openalex Percentile: Top 1%
Genomics and Rare Diseases
11.42
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.