Rare variant associations with plasma protein levels in the UK Biobank

In the paper

“However, their influence on the plasma proteome is largely unknown because previous rare variant proteogenomic studies have been limited in scale9,10.”

What the sources say

• Supported

  The Discussion (page unavailable) says few gene-based studies had used whole-genome sequencing to find rare-variant associations with proteins, and that low numbers of observations limit the power to detect rare-variant effects. This supports the claim that the influence of rare variants on plasma proteins remained incompletely understood because earlier work was limited in scale. (LLM, conf=0.84)

  cites [9] Kierczak, M. et al. Contribution of rare whole-genome sequencing variants to plasma protein levels and the missing heritability. Nat. Commun. 13, 2532 (2022). source
• Partly supported

  The Introduction (page unavailable) says earlier proteogenomic findings came nearly entirely from European populations using genotyping arrays, and the Discussion (page unavailable) describes this study as the largest of its kind in a Black population. This supports a gap in knowledge about genetic determinants of the plasma proteome, but the paper does not say that previous rare-variant proteogenomic studies were limited in scale or identify that as the reason rare variants’ influence was largely unknown. (LLM, conf=0.77)

  cites [10] Katz, D. H. et al. Whole genome sequence analysis of the plasma proteome in Black adults provides novel insights into cardiovascular disease. Circulation 145, 357–370 (2022). sourceExperimental — accuracy not yet measured

In the paper

“To date, most pQTLs have been discovered via genome-wide association studies (GWASs), which predominantly focus on common variants3,5–8.”

What the sources say

• Partly supported

  The paper describes its own genome–proteome-wide association study as identifying pQTLs (Abstract) and says it concentrated on common genetic variation (Discussion; page unavailable). It does not establish the broader claim that most pQTLs discovered to date came from GWASs. (LLM, conf=0.84)

  cites [3] Pietzner, M. et al. Mapping the proteo-genomic convergence of human diseases. Science 374, eabj1541 (2021). sourceExperimental — accuracy not yet measured
• Supported

  The Discovery of pQTLs section describes genome-wide mapping of 16.1 million variants and reports that only 5.5% of its primary associations had a minor allele frequency below 1%. The Cross-referencing with previously identified pQTLs section uses published proteomic GWAS and the GWAS Catalog to identify earlier discoveries. Together, these passages support the broad characterization, though they do not quantify the share of all historical pQTLs found by GWAS. (LLM, conf=0.84)

  cites [5] Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature https://doi.org/10.1038/s41586-023-06592-6 (2023). source
• Supported

  The Methods section ('Replication of previous pQTLs'; page unavailable) treats GWAS as a source of previously reported pQTLs. The paper also reports a genome-wide association analysis finding 1,927 pQTLs; its 'Genetic architecture of the plasma proteome' section identifies only 23 rare-variant and 208 low-frequency-variant associations, consistent with a predominant focus on common variants. (LLM, conf=0.85)

  cites [6] Sun, B. B. et al. Genomic atlas of the human plasma proteome. Nature 558, 73–79 (2018). source
• Partly supported

  The Results section, “Genome-wide meta-analysis of 90 proteins” (page unavailable), reports discovering hundreds of pQTLs through a GWAS meta-analysis, supporting GWAS as a pQTL discovery method. The paper does not establish that most pQTLs discovered to date came from GWAS or that GWAS predominantly focus on common variants; its Online Methods instead describe filtering by a minimum minor-allele count. (LLM, conf=0.79)

  cites [7] Folkersen, L. et al. Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals. Nat. Metab. 2, 1135–1148 (2020). sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [8] Ferkingstad, E. et al. Large-scale integration of the plasma proteome with genetics and disease. Nat. Genet. 53, 1712–1721 (2021). source

In the paper

“In a separate array-based GWAS on the UKB-PPP cohort, we tested for the association between common variants (MAF > 0.1%) and 2,922 protein assays, resulting in 14,287 primary genetic associations5.”

What the sources say

• Partly supported

  The 'Discovery of pQTLs' section reports testing 2,922 proteins and finding 14,287 primary associations, but those results came from a European-ancestry discovery subset of 34,557 participants, not the full UKB-PPP cohort. The 'Replication of pQTLs' section reports 23,588 primary associations for the full cohort. The methods describe imputed variants and a minor-allele-count filter, not the claimed MAF > 0.1% cutoff. (LLM, conf=0.88)

  cites [5] Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature https://doi.org/10.1038/s41586-023-06592-6 (2023). sourceExperimental — accuracy not yet measured

In the paper

“Using an n-of-one permutation analysis as previously described11, we identified P ≤ 1 × 10−8 as an appropriate P value threshold (Methods and Supplementary Table 3).”

What the sources say

• Supported

  The citation attaches to “n-of-one permutation analysis as previously described,” not to the citing authors’ own choice of P ≤ 1 × 10−8. The source’s Methods section describes using an n-of-1 permutation to set significance thresholds. It chose P ≤ 2 × 10−9 for its own analyses; that difference does not undermine the method citation. (LLM, conf=0.92)

  cites [11] Wang, Q. et al. Rare variant contribution to human disease in 281,104 UK Biobank exomes. Nature 597, 527–532 (2021). source

In the paper

“The effect sizes (β) of nominally significant ExWAS pQTLs (P < 1 × 10−4) strongly correlated with the GWAS-derived pQTLs5 (r2 = 0.96; Supplementary Fig. 2).”

What the sources say

• Supported

  The citation is attached to “GWAS-derived pQTLs,” identifying the source of the comparison data. The source’s Discovery of pQTLs section reports genome-wide mapping of genetic variants to protein levels. The r² = 0.96 comparison is presented as the citing paper’s own Supplementary Fig. 2 result, not as a finding attributed to this source. (LLM, conf=0.90)

  cites [5] Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature https://doi.org/10.1038/s41586-023-06592-6 (2023). source

In the paper

“ASGR1, which encodes a subunit of the asialoglycoprotein receptor, also emerged as a hotspot in the UKB-PPP GWAS and other large pQTL studies5,6,8.”

What the sources say

• Supported

  Figure 2 labels ASGR1 with 359 associated protein targets; its caption explains that regions with more than 100 targets are labelled. This supports calling ASGR1 a hotspot in this paper’s UKB-PPP GWAS. The separate claim about other pQTL studies is accompanied by other citations and is not established by this paper’s figure. (LLM, conf=0.92)

  cites [5] Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature https://doi.org/10.1038/s41586-023-06592-6 (2023). source
• ?Could not verify

  The ‘trans pQTLs identify pathways to disease’ section describes twelve hotspot regions and names examples, but does not identify ASGR1 as one. Searches for ASGR1 and the asialoglycoprotein receptor found no passage in our copy establishing the claimed ASGR1 hotspot. (LLM, conf=0.72)

  cites [6] Sun, B. B. et al. Genomic atlas of the human plasma proteome. Nature 558, 73–79 (2018). sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [8] Ferkingstad, E. et al. Large-scale integration of the plasma proteome with genetics and disease. Nat. Genet. 53, 1712–1721 (2021). source

In the paper

“This likely reflects the enrichment of HBB PTVs in individuals of South Asian ancestries, as observed in our UKB PheWAS11.”

What the sources say

• Partly supported

  The Pan-ancestry collapsing analysis reports a significant association between HBB protein-truncating variants and thalassaemia in participants of South Asian ancestry. It does not report that HBB PTVs are enriched in that group relative to other ancestries or connect them to an HBB–SLC16A1 association, so it supports only part of the attributed explanation. (LLM, conf=0.83)

  cites [11] Wang, Q. et al. Rare variant contribution to human disease in 281,104 UK Biobank exomes. Nature 597, 527–532 (2021). sourceExperimental — accuracy not yet measured

In the paper

“We found a significant enrichment of ClinVar15 pathogenic and likely pathogenic variants among the 1,484 significant rare missense and in-frame indel cis-CDS pQTLs (observed: 3.5%; expected: 0.54%; two-tail binomial P = 2.5 × 10−25; Extended Data Fig. 3a).”

What the sources say

• Supported

  The Introduction describes ClinVar as an archive of human variants and interpretations of their clinical significance, and ‘Improvements to Searching ClinVar’ discusses its pathogenic classifications (pages not specified). The citation identifies the source of the variant classifications; the enrichment and statistical figures are presented as the citing authors’ own findings, not attributed to this paper. (LLM, conf=0.90)

  cites [15] Landrum, M. J. et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46, D1062–D1067 (2018). source

In the paper

“For example, PTVs in EPOR, encoding the erythropoietin receptor, were associated with increased erythropoietin, an example of compensatory upregulation (‘ptv’ model; P = 3.5 × 10−24; β = 1.78; 95% confidence interval (CI), 1.43 to 2.12)28.”

What the sources say

• ?Could not verify

  The Results (Table 1; page unavailable) report an association between a cis-EPO variant and circulating EPO levels, not an analysis of protein-truncating variants in EPOR. Searches of our copy for EPOR, protein-truncating variants, compensatory upregulation, and the stated P value found no passage reporting the claimed association or statistics. (LLM, conf=0.76)

  cites [28] Harlow, C. E. et al. Identification and single-base gene-editing functional validation of a cis-EPO variant as a genetic predictor for EPO-increasing therapies. Am. J. Hum. Genet. 109, 1638–1652 (2022). sourceExperimental — accuracy not yet measured

In the paper

“Ten of the 20 PTVs associated with increased protein abundances (50%) were predicted to escape nonsense-mediated decay because they occurred within the last exon, the penultimate exon within 50 base pairs (bp) of the 3′ junction or the first exon within the first 200 nucleotides of the coding sequence12.”

What the sources say

• ?Could not verify

  The supplied passage has no section or page label and contains only links, not findings about protein abundance or nonsense-mediated decay. Searches for the 10-of-20 PTV count and the stated exon-position criteria returned the same links, so our copy does not verify the claim. (LLM, conf=0.75)

  cites [12] Coban-Akdemir, Z. et al. Identifying genes whose mutant transcripts cause dominant disease traits by potential gain-of-function alleles. Am. J. Hum. Genet. 103, 171–187 (2018). sourceExperimental — accuracy not yet measured

In the paper

“There were also 22 trans-CDS associations between known ligand–receptor pairs37 (Supplementary Table 11).”

What the sources say

• Supported

  The Results section, “Identification of putative ligand–receptor pairs” (page unavailable), reports a compiled set of known interacting ligand–receptor pairs. Citation 37 follows “known ligand–receptor pairs” and supports that identification; the count of 22 trans-CDS associations is presented as the citing paper’s result, with its own Supplementary Table 11. (LLM, conf=0.88)

  cites [37] Ramilowski, J. A. et al. A draft network of ligand-receptor-mediated multicellular signalling in human. Nat. Commun. 6, 7866 (2015). source

In the paper

“Moreover, there were only three significant gene-level cis-CDS pQTLs in the synonymous (syn) collapsing model19,20 (full definitions of collapsing models can be found in Extended Data Table 1).”

What the sources say

• ?Could not verify

  The Extended Data passages discuss effects of synonymous mutations on yeast fitness and mRNA levels, not gene-level cis-CDS pQTLs. Searches for “cis-CDS pQTLs,” “synonymous collapsing model,” and “pQTL” found no passage reporting three significant associations. (LLM, conf=0.76)

  cites [19] Shen, X., Song, S., Li, C. & Zhang, J. Synonymous mutations in representative yeast genes are mostly strongly non-neutral. Nature 606, 725–731 (2022). sourceExperimental — accuracy not yet measured
• Partly supported

  The Methods section describes a synonymous-variant gene-based collapsing model, supporting the model cited in the sentence. But the reported results concern UK Biobank clinical phenotypes, not cis-CDS pQTLs; the paper does not support the count of three significant pQTLs. (LLM, conf=0.82)

  cites [20] Dhindsa, R. S. et al. A minimal role for synonymous variation in human disease. Am. J. Hum. Genet. 109, 2105–2109 (2022). sourceExperimental — accuracy not yet measured

In the paper

“By contrast, the 36,466 missense variants and in-frame indels that were not associated with cis changes in protein abundances (P > 1 × 10−4) were significantly depleted of ClinVar pathogenic/likely pathogenic variants (observed: 0.4%; expected: 0.54%; two-tail binomial P = 1.1 × 10−4).”

What the sources say

• Partly supported

  Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.

  cites [15] Landrum, M. J. et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46, D1062–D1067 (2018). sourceExperimental — accuracy not yet measured

In the paper

“most rare variant pQTLs (MAF ≤ 0.1%) were not detected in the common variant analysis on the same cohort5.”

What the sources say

• ?Could not verify

  The Discovery of pQTLs section reports associations with MAF below 1% and 0.5%, but does not compare pQTLs at MAF ≤ 0.1% with a common-variant analysis of the same cohort. I searched for that threshold and comparison; the Non-European pQTL mapping section discusses a different comparison, across ancestry groups. (LLM, conf=0.72)

  cites [5] Sun, B. B. et al. Plasma proteomic associations with genetics and health in the UK Biobank. Nature https://doi.org/10.1038/s41586-023-06592-6 (2023). sourceExperimental — accuracy not yet measured

In the paper

“In total, 1,487 (51%) distinct genes carried at least one of these 5,025 missense variants11.”

What the sources say

• ?Could not verify

  The Variant-level associations section reports 326 significant missense variants, and the Methods section describes aggregating variants by gene, but neither gives the claimed count of 5,025 variants or 1,487 genes (51%). Searches for both numbers and for the gene-level proportion found no passage substantiating the claim in our copy. (LLM, conf=0.75)

  cites [11] Wang, Q. et al. Rare variant contribution to human disease in 281,104 UK Biobank exomes. Nature 597, 527–532 (2021). sourceExperimental — accuracy not yet measured

In the paper

“Many of the downregulated proteins are markers of other haematopoietic lineages, such as KIR2DL2 and KIR2DL3 (natural killer cell activation)52, and PRG2 and PRG3 (constituents of eosinophil granules also involved in basophil stimulation)53,54.”

What the sources say

• ?Not checked — no full text of the sourcecites [52] Colonna, M. & Samaridis, J. Cloning of immunoglobulin-superfamily members associated with HLA-C and HLA-B recognition by human natural killer cells. Science 268, 405–408 (1995). source
• Partly supported

  The introduction (p. 1981) identifies major basic protein as a constituent of eosinophil granules, and the discussion (p. 1988–1989) reports its activation of human basophils. The cited paper does not identify PRG2 or PRG3 by those names or establish the stated role for both proteins; the downregulation finding belongs to the citing study, not this citation. (LLM, conf=0.84)

  cites [53] O’Donnell, M. C., Ackerman, S. J., Gleich, G. J. & Thomas, L. L. Activation of basophil and mast cell histamine release by eosinophil granule major basic protein. J. Exp. Med. 157, 1981–1991 (1983). sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites [54] Plager, D. A. et al. Comparative structure, proximal promoter elements, and chromosome location of the human eosinophil major basic protein genes. Genomics 71, 271–281 (2001). source

In the paper

“Three of the JAK2 trans-CDS pQTLs are proteins involved in the integrin β2 pathway: FCGR2A, GP1BA and ICAM2 (ref. 45) (Fig. 3a).”

What the sources say

• ?Could not verify

  The Introduction describes PID as a database of human signaling and regulatory pathways, and the Web Interface and Application section explains how to retrieve a pathway’s participating molecules (page numbers unavailable). Our copy does not identify FCGR2A, GP1BA or ICAM2 as members of an integrin β2 pathway, or discuss JAK2 trans-CDS pQTLs. Searches for those protein names, integrin β2 and JAK2 did not find a passage establishing the claim. (LLM, conf=0.74)

  cites [45] Schaefer, C. F. et al. PID: the Pathway Interaction Database. Nucleic Acids Res. 37, D674–679 (2009). sourceExperimental — accuracy not yet measured

In the paper

“The three other proteins increased in abundance in TET2-CH were CD1C (a marker of conventional dendritic cells), CLEC4C (a marker of plasmacytoid dendritic cells) and CD86 (a marker of dendritic cells, monocytes and other antigen-presenting cells)51.”

What the sources say

• Partly supported

  The cDC2 Phenotype and distribution section identifies CD1c as expressed by conventional dendritic cells, and the plasmacytoid dendritic cell Phenotype and distribution section explicitly lists CLEC4C as a marker. The copy does not substantiate the CD86 marker description (searched: CD86). The citation appears to support the marker descriptions, not the citing authors’ TET2-CH abundance finding. (LLM, conf=0.86)

  cites [51] Collin, M. & Bigley, V. Human dendritic cell subsets: an update. Immunology 154, 3–20 (2018). sourceExperimental — accuracy not yet measured

In the paper

“Interestingly, there were no significant associations between these three variants and clinically relevant phenotypes in our published PheWAS of 470,000 UKB exomes (https://azphewas.com)11, suggesting that pharmacologic inhibition of NLRC4 may be safe.”

What the sources say

• Partly supported

  The Main section describes a UK Biobank exome PheWAS, and the Discussion says its results are available at azphewas.com. But the paper reports 281,104 participants, not 470,000, and our copy does not report whether the three NLRC4 variants had significant associations with clinically relevant phenotypes (searched: NLRC4). (LLM, conf=0.86)

  cites [11] Wang, Q. et al. Rare variant contribution to human disease in 281,104 UK Biobank exomes. Nature 597, 527–532 (2021). sourceExperimental — accuracy not yet measured

In the paper

“For example, 29% of genes with at least one trans-CDS association in the collapsing analyses (n = 73 of 254) are targets of currently approved drugs listed in DrugBank (expected: 14%; two-tailed binomial P = 8.7 × 10−10)41.”

What the sources say

• Supported

  The Database Description states that DrugBank includes FDA-approved drugs and links drug entries to protein targets, supporting the citation's identification of DrugBank as the drug-target resource. The 73-of-254 result, expected percentage, and P value are presented as the citing authors' own analysis, not as findings attributed to DrugBank. (LLM, conf=0.88)

  cites [41] Wishart, D. S. et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res. 34, D668–672 (2006). source

In the paper

“The effect sizes of the ‘URmtr’-derived cis-CDS pQTLs (mean |β| = 1.62) were significantly larger than the ‘UR’ ones (mean |β| = 1.45; Wilcoxon P = 1.2 × 10−5) (Fig. 2c).”

In the paper

“There was also strong directional concordance between the ExWAS-derived pQTLs and pQTLs detected in an independent Icelandic population8, which had increased resolution for rarer variants (MAF > 0.01%; Supplementary Note).”

What the sources say

• ?Not checked — no full text of the sourcecites [8] Ferkingstad, E. et al. Large-scale integration of the plasma proteome with genetics and disease. Nat. Genet. 53, 1712–1721 (2021). source

In the paper

“Four were annotated as loss of splice donor or acceptor sites, which can have more variable effects than frameshift and nonsense variants.”

In the paper

“Interestingly, 20 of the 77 (26%) proteins associated with STAB1 variants were also associated with STAB2 variants.”

In the paper

“One missense variant in GOT1 had a suggestive association with reduced aspartate aminotransferase in the proteogenomic ExWAS.”

In the paper

“As expected, 99% (n = 687 of 691) of the cis signals from the ptv model were associated with decreased protein levels (Fig. 2c).”

In the paper

“As expected, given the constraints of GWAS, only 19% of the rare (MAF ≤ 0.1%) associations from our ExWAS were significant in the UKB-PPP GWAS.”

In the paper

“Moreover, the rare significant (P ≤ 1 × 10−8) and suggestive (1 × 10−8 < P ≤ 1 × 10−4) missense cis-CDS pQTLs were more likely to be predicted damaging by the in silico predictor, REVEL16 (Extended Data Fig. 3b).”

What the sources say

• ?Not checked — no full text of the sourcecites [16] Ioannidis, N. M. et al. REVEL: an ensemble method for predicting the pathogenicity of rare missense variants. Am. J. Hum. Genet. 99, 877–885 (2016). source

In the paper

“For 47 of these 50 genes (94%), at least 75% of the significant missense pQTLs were associated with decreased protein abundance.”

In the paper

“All six variants were also significantly (P ≤ 1 × 10−8) associated with low-density lipoprotein levels in the expected direction (Supplementary Table 7).”

In the paper

“For example, there were significant associations between PTVs in PSAP and increased progranulin (GRN; P = 5.5 × 10−17; β = 2.60; 95% CI, 1.99 to 3.21) and cathepsin B (P = 1.2 × 10−11; β = 2.10; 95% CI, 1.49 to 2.70), and a nearly significant association with increased cathepsin D (P = 9.0 × 10−8; β = 1.61; 95% CI, 1.02 to 2.20) (Supplementary Table 8).”

In the paper

“Among 1,084 gene–protein associations specifically arising from the ptv model, 667 (62%) were not significant in the ExWAS.”

In the paper

“Likewise, we identified a trans association between mutations in FLT3, encoding the fms-related tyrosine kinase 3, and increased levels of the FLT3 ligand (FLT3LG; ‘ptvraredmg’ model; P = 1.2 × 10−22; β = 0.85; 95% CI, 0.68 to 1.02).”

In the paper

“Notably, 501 (25.5%) of the 1,962 gene–protein abundance signals identified in the collapsing analysis did not reach significance in the ExWAS (Extended Data Fig. 4a).”

In the paper

“For example, there were significant associations between PTVs in PSAP and increased progranulin (GRN; P = 5.5 × 10−17; β = 2.60; 95% CI, 1.99 to 3.21) and cathepsin B (P = 1.2 × 10−11; β = 2.10; 95% CI, 1.49 to 2.70), and a nearly significant association with increased cathepsin D (P = 9.0 × 10−8; β = 1.61; 95% CI, 1.02 to 2.20) (Supplementary Table 8).”

In the paper

“Moreover, among the common cis-CDS pQTLs, the proportions of PTVs and missense, synonymous and non-coding variants closely matched the proportions observed for the total variants included in the ExWAS (that is, the expected null distribution; Fig. 1c).”

In the paper

“For example, there was a significant association between non-synonymous variants in TSHR, encoding the thyroid stimulating hormone receptor, and increased thyroid stimulating hormone (TSHB) (‘flexdmg’ model; P = 1.6 × 10−31; β = 0.66; 95% CI, 0.55 to 0.76).”

In the paper

“The percentage of protein-lowering missense variants in the remaining three genes ranged from 14% to 50% (Supplementary Table 2).”

In the paper

“In total, there were 7,412 significant associations across the nine non-synonymous QV models (Fig. 2a).”

In the paper

“Another example that only became significant in the pan-ancestry analysis was the trans association between PTVs in ATM, associated with ataxia telangiectasia and several cancers, and increased levels of alpha-fetoprotein (P = 1.8 × 10−9, β = 0.25, 95% CI, 0.17 to 0.33)31.”

What the sources say

• ?Not checked — no full text of the sourcecites [31] Waldmann, T. A. & McIntire, K. R. Serum-α-fetoprotein levels in patients with ataxia-telangiectasia. Lancet 2, 1112–1115 (1972). source

In the paper

“In comparison, PTVs and missense variants encompassed a significantly larger percentage of rare (MAF ≤ 0.1%) and ultra-rare (MAF ≤ 0.01%) cis-CDS pQTLs (Fig. 1c and Supplementary Table 5).”

In the paper

“Rare cis associations also had larger magnitudes of effect (median |β| = 1.86) than rare trans associations (median |β| = 1.26; Wilcoxon P < 10−300) (Extended Data Fig. 2b).”

In the paper

“Most pQTLs identified in the collapsing analysis were associated with changes in the abundance of a single protein (Fig. 2b).”

In the paper

“The models that included PTVs alongside putatively damaging missense variants encompassed most of the 4,528 cis-CDS signals.”

In the paper

“Meanwhile, only 112 of the rare PTV signals from the ExWAS did not achieve significance in the PTV collapsing model (Extended Data Fig. 4b).”

In the paper

“For example, three rare protein-coding variants in NLRC4 were associated with significant changes in plasma levels of the proinflammatory cytokine IL-18 in the ExWAS (Extended Data Table 2 and Supplementary Table 2).”

In the paper

“As expected, the median absolute effect size (β) of rare cis-CDS pQTLs was 1.85, compared with 0.3 for common cis-CDS pQTLs (Wilcoxon P < 10−300).”

In the paper

“Among the 254 genes with trans-CDS associations, 87% were associated with three or fewer proteins.”

In the paper

“Of the 2,227 rare cis-CDS pQTLs, 538 (24.2%) were PTVs (Fig. 1d and Supplementary Table 5).”

In the paper

“Similarly, the absolute effect sizes of rare trans-CDS pQTLs (median |β| = 1.26) were significantly larger than those of common trans-CDS pQTLs (median |β| = 0.08; Wilcoxon P < 10−300) (Extended Data Fig. 2a).”

In the paper

“Most often, rare missense variants within the same gene had a similar effect on protein abundance.”

In the paper

“In this combined analysis, there were 752 unique study-wide significant gene–protein abundance associations that were not significant in the European-only analyses.”

In the paper

“On the other hand, 228 associations that were significant in the European-only analyses did not reach study-wide significance in the pan-ancestry analysis (Supplementary Tables 8 and 10).”

In the paper

“One newly significant example was the trans association between PTVs in HBB and increased levels of the monocarboxylic acid transporter SLC16A1 (β = 1.85; 95% CI, 1.33 to 2.37; P = 3.2 × 10−12).”

In the paper

“However, certain genes appeared to be pQTL ‘hotspots’, associated with over 20 different protein abundances, including ASGR1 (n = 186), STAB1 (n = 77), STAB2 (n = 41) and GNPTAB (n = 37) (Fig. 2a,b).”

In the paper

“Furthermore, 90% of the more common study-wide associations (MAF > 0.1%) in our study were also significant in the GWAS (Fig. 1b).”

In the paper

“Meanwhile, only 77 (21%) of the 372 significant trans signals from the ptv model were associated with decreased protein levels.”

In the paper

“As expected, nearly all the PTVs were associated with decreased protein abundances (n = 518 of 538; 96%).”

In the paper

“Of the associations that only reached significance in the collapsing analysis, 101 (20.2%) were cis-CDS (Supplementary Table 8).”

In the paper

“The signals from the remaining nine significant genes in the PTV-only model were attenuated in the plasma pQTL-informed missense models (Supplementary Table 15).”

In the paper

“Encouragingly, there was complete concordance across panels (Supplementary Table 18).”

In the paper

“In the ExWAS, this variant was associated with altered levels of ASS1 (P = 1.4 × 10−12; β = −0.05; 95% CI, −0.04 to −0.06), CES3 (P = 2.9 × 10−12; β = 0.07; 95% CI, 0.08 to 0.05), FUOM (P = 1.7 × 10−10; β = −0.05; 95% CI, −0.03 to −0.06), HYAL1 (P = 9.5 × 10−9; β = −0.04; 95% CI, −0.03 to −0.06), SHBG (P = 1.9 × 1−13; β = −0.05; 95% CI, −0.04 to −0.06) and SMPD1 (P = 2.7 × 10−11; β = −0.05; 95% CI”

In the paper

“There was also a newly significant association between TCN1, encoding a vitamin B12 binding protein, and vitamin B deficiency.”

In the paper

“In the ExWAS, this variant was associated with altered levels of ASS1 (P = 1.4 × 10−12; β = −0.05; 95% CI, −0.04 to −0.06), CES3 (P = 2.9 × 10−12; β = 0.07; 95% CI, 0.08 to 0.05), FUOM (P = 1.7 × 10−10; β = −0.05; 95% CI, −0.03 to −0.06), HYAL1 (P = 9.5 × 10−9; β = −0.04; 95% CI, −0.03 to −0.06), SHBG (P = 1.9 × 1−13; β = −0.05; 95% CI, −0.04 to −0.06) and SMPD1 (P = 2.7 × 10−11; β = −0.05; 95% CI”

In the paper

“At this P ≤ 1 × 10−8 threshold, the expected number of collapsing pQTL false positives is 4 out of the 7,412 (0.05%) observed significant associations.”

In the paper

“The P value of the association between PCSK9 and dyslipidaemia markedly improved from P = 4.02 × 10−17 (odds ratio (OR) = 0.35; 95% CI, 0.27 to 0.46) to P = 7.69 × 10−112 (OR = 0.63; 95% CI, 0.60 to 0.65) in the ptvolink2pcnt model.”

In the paper

“At this P ≤ 1 × 10−8 threshold, the expected number of ExWAS pQTL false positives is 24 out of the 328,975 observed significant associations (0.007%).”

In the paper

“In the ExWAS, this variant was associated with altered levels of ASS1 (P = 1.4 × 10−12; β = −0.05; 95% CI, −0.04 to −0.06), CES3 (P = 2.9 × 10−12; β = 0.07; 95% CI, 0.08 to 0.05), FUOM (P = 1.7 × 10−10; β = −0.05; 95% CI, −0.03 to −0.06), HYAL1 (P = 9.5 × 10−9; β = −0.04; 95% CI, −0.03 to −0.06), SHBG (P = 1.9 × 1−13; β = −0.05; 95% CI, −0.04 to −0.06) and SMPD1 (P = 2.7 × 10−11; β = −0.05; 95% CI”

In the paper

“cis-CDS pQTLs corresponding to PTVs were nearly always associated with decreased protein levels”

In the paper

“In total, 24 of 5.4 billion permuted tests had P ≤ 1 × 10−8 (Supplementary Table 3).”

In the paper

“We identified 5,025 missense variants with cis-acting negative betas (P < 0.0001) among the genes encoding the 2,923 Olink protein analytes.”

In the paper

“Consistent with related binary phenotypes, the associations of PCSK9, ANGPTL4, LPL and ANGPTL3 with lipid-related traits all improved under the ptvolink and ptvolink2pcnt models.”

In the paper

“rare cis- and trans-CDS pQTLs conferred significantly larger effect sizes than common variant pQTLs.”

In the paper

“In the ExWAS, this variant was associated with altered levels of ASS1 (P = 1.4 × 10−12; β = −0.05; 95% CI, −0.04 to −0.06), CES3 (P = 2.9 × 10−12; β = 0.07; 95% CI, 0.08 to 0.05), FUOM (P = 1.7 × 10−10; β = −0.05; 95% CI, −0.03 to −0.06), HYAL1 (P = 9.5 × 10−9; β = −0.04; 95% CI, −0.03 to −0.06), SHBG (P = 1.9 × 1−13; β = −0.05; 95% CI, −0.04 to −0.06) and SMPD1 (P = 2.7 × 10−11; β = −0.05; 95% CI”

In the paper

“There were two associations where the flexnonsyn model outperformed the ptvolink model (PROC with thrombophlebitis and LCAT with HDL cholesterol; Fig. 4b and Extended Data Fig. 5).”

In the paper

“the rare missense cis-CDS pQTLs are enriched for pathogenic and predicted damaging missense variants.”

In the paper

“The P values of the UKB-PPP excluded models and full models were highly correlated (R > 0.99; Supplementary Fig. 4).”

In the paper

“Impressively, 15 genes that were not significant in the standard ptv model became significant in at least one of the pQTL-informed models (Fig. 4b and Supplementary Table 15).”

In the paper

“There was also an association between EPO and reduced haematocrit that was only significant in the ptvolink2pcnt model (P = 1.8 × 10−83; β = −0.24; 95% CI, −0.27 to −0.22).”

In the paper

“Most of the significant (P ≤ 1 × 10−8) associations arose with a VAF ≥ 10% cut-off (Supplementary Table 13).”

In the paper

“In the ExWAS, this variant was associated with altered levels of ASS1 (P = 1.4 × 10−12; β = −0.05; 95% CI, −0.04 to −0.06), CES3 (P = 2.9 × 10−12; β = 0.07; 95% CI, 0.08 to 0.05), FUOM (P = 1.7 × 10−10; β = −0.05; 95% CI, −0.03 to −0.06), HYAL1 (P = 9.5 × 10−9; β = −0.04; 95% CI, −0.03 to −0.06), SHBG (P = 1.9 × 1−13; β = −0.05; 95% CI, −0.04 to −0.06) and SMPD1 (P = 2.7 × 10−11; β = −0.05; 95% CI”

In the paper

“epitope effects do not seem to systematically confound these coding pQTLs.”

In the paper

“Several quantitative trait associations also became more significant in these models (Extended Data Fig. 6 and Supplementary Table 16).”

In the paper

“In the ExWAS, this variant was associated with altered levels of ASS1 (P = 1.4 × 10−12; β = −0.05; 95% CI, −0.04 to −0.06), CES3 (P = 2.9 × 10−12; β = 0.07; 95% CI, 0.08 to 0.05), FUOM (P = 1.7 × 10−10; β = −0.05; 95% CI, −0.03 to −0.06), HYAL1 (P = 9.5 × 10−9; β = −0.04; 95% CI, −0.03 to −0.06), SHBG (P = 1.9 × 1−13; β = −0.05; 95% CI, −0.04 to −0.06) and SMPD1 (P = 2.7 × 10−11; β = −0.05; 95% CI”

In the paper

“we ran the synonymous (empirical null) collapsing model and found only seven events achieved a signal below this threshold.”

In the paper

“Likewise, the ANGPTL3-dyslipidaemia signal improved from P = 8.73 × 10−9 (OR = 0.58; 95% CI, 0.48 to 0.70) to P = 9.62 × 10−17 (OR = 0.57; 95% CI, 0.50 to 0.66) in the ptvolink model.”

In the paper

“In the standard ptv model, 11 genes with at least one qualifying cis-CDS missense pQTL were significantly associated with at least one phenotype (Supplementary Table 15).”

In the paper

“Only 4 of 499.9 million permuted tests had P ≤ 1 × 10−8 (Supplementary Table 3).”

In the paper

“we identified an additional 382 cautionary variants (Supplementary Table 17) on top of the original 8,365 previously described.”

In the paper

“Genomic inflation was well-controlled (median λGC = 1.03; 95% range, 1.01–1.05; Supplementary Fig. 1 and Supplementary Table 4).”

In the paper

“We performed rigorous sample-level quality control (Methods), leaving 49,736 (92%) multi-ancestry samples with exomes for downstream analyses.”

In the paper

“This relatively low percentage of cis-position, trans-CDS associations compared with the ExWAS (5% versus 52%) highlights the strength of collapsing analysis in mitigating contamination due to linkage disequilibrium.”

In the paper

“These data demonstrate how collapsing analyses increase statistical power for discovering rare variant-driven associations.”

In the paper

“These results collectively demonstrate that the cis-CDS pQTLs are enriched for biologically relevant signals.”

In the paper

“The n-of-1 permutation analysis and the synonymous QV model converged on P ≤ 1 × 10−8 as an appropriately conservative P value threshold (Supplementary Table 3 and Methods).”

In the paper

“These results illustrate how linkage disequilibrium contaminates common pQTLs, making it challenging to ascribe causality to these variants without fine-mapping.”

In the paper

“This underscores the ability of population genetics-based methods to prioritize functional missense variants, offering complementary information to in silico pathogenicity predictors.”

In the paper

“These results demonstrate how including cis-CDS missense pQTLs can enhance conventional loss-of-function gene collapsing analyses.”

In the paper

“Strikingly, there was very little overlap between the protein abundances associated with each of these five genes, suggesting distinct downstream effects of the somatic events detected in each.”

In the paper

“Moreover, these data show that some rare, putative gain-of-function mutations in this gene may not be sufficient to cause an observable phenotype, highlighting the value of this resource in clinical diagnostic settings.”

In the paper

“We then pruned this cohort for sample duplicates and first-degree genetic relatedness (no pair with a kinship coefficient exceeding 0.1769, n = 462), resulting in 49,736 (95%) participants available for the multi-ancestry analyses performed in this paper.”

In the paper

“we had previously created dummy phenotypes to correspond to each of the five exome sequence delivery batches to identify and exclude from analyses 46 genes that were enriched for exome sequencing batch effects”