A major goal of biomedicine is to understand the function of every gene in the human genome1. Loss-of-function mutations can disrupt both copies of a given gene in humans and phenotypic analysis of such ‘human knockouts’ can provide insight into gene function. Consanguineous unions are more likely to result in offspring carrying homozygous loss-of-function mutations. In Pakistan, consanguinity rates are notably high2. Here we sequence the protein-coding regions of 10,503 adult participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS), designed to understand the determinants of cardiometabolic diseases in individuals from South Asia3. We identified individuals carrying homozygous predicted loss-of-function (pLoF) mutations, and performed phenotypic analysis involving more than 200 biochemical and disease traits. We enumerated 49,138 rare (<1% minor allele frequency) pLoF mutations. These pLoF mutations are estimated to knock out 1,317 genes, each in at least one participant. Homozygosity for pLoF mutations at PLA2G7 was associated with absent enzymatic activity of soluble lipoprotein-associated phospholipase A2; at CYP2F1, with higher plasma interleukin-8 concentrations; at TREH, with lower concentrations of apoB-containing lipoprotein subfractions; at either A3GALT2 or NRG4, with markedly reduced plasma insulin C-peptide concentrations; and at SLC9A3R1, with mediators of calcium and phosphate signalling. Heterozygous deficiency of APOC3 has been shown to protect against coronary heart disease4, 5; we identified APOC3 homozygous pLoF carriers in our cohort. We recruited these human knockouts and challenged them with an oral fat load. Compared with family members lacking the mutation, individuals with APOC3 knocked out displayed marked blunting of the usual post-prandial rise in plasma triglycerides. Overall, these observations provide a roadmap for a ‘human knockout project’, a systematic effort to understand the phenotypic consequences of complete disruption of genes in humans.
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Extended data figures and tables
Extended Data Figures
- Extended Data Figure 1: pLoF mutations are typically seen in very few individuals. (172 KB)
The site-frequency spectrum of synonymous, missense, and high-confidence pLoF mutations is represented. Points represent the proportion of variants within a 1 × 10−4 minor allele frequency bin for each variant category. Lines represent the cumulative proportions of variants categories. The bottom inset highlights that most pLoF variants are often seen in no more than one or two individuals. The top inset highlights that virtually all pLoF mutations are very rare.
- Extended Data Figure 2: Intersection of homozygous pLoF genes between PROMIS and other cohorts. (115 KB)
We compared the counts and overlap of unique homozygous pLoF genes in PROMIS with other exome sequenced cohorts.
- Extended Data Figure 3: QQ-plot of recessive model pLoF association analysis across phenotypes. (53 KB)
Analyses to determine whether homozygous pLoF carrier status was associated with traits was performed where there were at least two homozygous pLoF carriers phenotyped per trait. The observed versus the expected results from 15,263 associations are displayed here demonstrating an excess of associations beyond a Bonferroni threshold.
- Extended Data Figure 4: Carriers of pLoF alleles in CYP2F1 have increased IL-8 concentrations. (46 KB)
Participants who had pLoF mutations in the CYP2F1 gene had higher concentrations of IL-8, whereas heterozygotes had a more modest effect when compared to the rest of the cohort of non-carriers. IL-8 concentration is natural log transformed. Bars represent 1.5× interquartile range beyond the 25th and 75th percentiles.
- Extended Data Figure 5: Carriers of pLoF alleles in TREH have decreased concentrations of several lipoprotein subfractions. (135 KB)
Participants who had pLoF mutations in the TREH gene had lower concentrations of several lipoprotein subfractions. Bars represent 1.5× interquartile range beyond the 25th and 75th percentiles.
- Extended Data Figure 6: Nondiabetic homozygous pLoF carriers for A3GALT2 have diminished insulin C-peptide concentrations. (49 KB)
Among nondiabetics, those who were homozygous pLoF for A3GALT2 had substantially lower fasting insulin C-peptide concentrations. This observation was not evident in nondiabetic heterozygous pLoF A3GALT2 participants. Insulin C-peptide is natural log transformed. Bars represent 1.5× interquartile range beyond the 25th and 75th percentiles.
- Extended Data Figure 7: Example of a second polymorphism in-phase which rescues a putative protein-truncating mutation. (104 KB)
Short-reads that align to genomic positions 65,339,112 to 65,339,132 on chromosome 1 are displayed for one individual with a putative homozygous pLoF genotype in this region. The SNP at position 65,339,122 from G to T is annotated as a nonsense mutation in the JAK1 gene. However, all three homozygotes of this mutation carried a tandem SNP in the same codon (A to G at 65,339,124) thus resulting in a glutamine and effectively rescuing the protein-truncating mutation.
- Extended Data Figure 8: Anticipated number of genes knocked out with increasing sample sizes by minimum knockout count. (68 KB)
We simulate the number of genes expected to be knocked out by minimum knockout count per gene at increasing sample sizes. We perform this simulation with and without the observed inbreeding.
- Extended Data Figure 9: PROMIS participants have an excess burden of runs of homozygosity compared with other populations. (37 KB)
Consanguinity leads to regions of genomic segments that are identical by descent and can be observed as runs of homozygosity. Using genome-wide array data in 17,744 PROMIS participants and reference samples from the International HapMap3, the burden of runs of homozygosity (minimum 1.5 Mb) per individual was derived and population-specific distributions are displayed, with outliers removed. This highlights the higher median runs of homozygosity burden in PROMIS and the higher proportion of individuals with very high burdens.
- Extended Data Figure 10: Down-sampling of synonymous and high confidence pLoF variants to validate simulation. (37 KB)
a, b, We ran simulations to estimate the number of unique, completely knocked out genes at increasing sample sizes. Before applying our model, we first applied this approach to a range of sample sizes below 7,078 for variants that were not under constraint, synonymous variants (a), and for high-confidence null variants (b). At the observed sample size, we did not observe significant selection. We expect that at increasing sample sizes, there may be a subset of genes that will not be tolerated in a homozygous pLoF state. In fact, our estimates are slightly more conservative when comparing outbred simulations with a recent description of >100,000 Icelanders using a more liberal definition for pLoF mutations.
- Supplementary Information (621 KB)
This file contains Supplementary Tables 1-9, the full legend for Supplementary Table 1 (supplied as a separate spreadsheet) and Supplementary References.
- Supplementary Table (241 KB)
This file contains Supplementary Table 1 – see the Supplementary Information document for the full description.