The genetic regulation of protein expression in cerebrospinal fluid
Open accessAbstract
Studies of the genetic regulation of cerebrospinal fluid (CSF) proteins may reveal pathways for treatment of neurological diseases. 398 proteins in CSF were measured in 1,591 participants from the BioFINDER study. Protein quantitative trait loci (pQTL) were identified as associations between genetic variants and proteins, with 176 pQTLs for 145 CSF proteins ( P < 1.25 × 10 −10 , 117 cis ‐pQTLs and 59 trans ‐pQTLs). Ventricular volume (measured with brain magnetic resonance imaging) was a confounder for several pQTLs. pQTLs for CSF and plasma proteins were overall correlated, but CSF‐specific pQTLs were also observed. Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease. CSF levels of GRN, MMP‐10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively. These findings point to pathways to be explored for novel therapies. The novel finding that ventricular volume confounded pQTLs has implications for design of future studies of the genetic regulation of the CSF proteome.
AI snapshot
Written from the paper’s full text.
TL;DR
Genome-wide analysis of 398 CSF proteins in 1,591 BioFINDER participants identified 176 pQTLs for 145 proteins and nominated proteins with shared genetic effects in Alzheimer’s disease, Parkinson’s disease, ALS, and other brain-related traits. CSF and plasma pQTLs were correlated but not identical, and ventricular volume was identified as a confounder for several CSF pQTLs.
Key findings
- In CSF, 176 pQTLs were associated with 145 proteins at Bonferroni significance (P < 1.253 × 10−10), including 117 cis-pQTLs and 59 trans-pQTLs; plasma analyses found 197 pQTLs among 153 proteins.
- CSF and plasma pQTLs were highly correlated overall (Spearman Rho = 0.69, P < 0.001), but 74 of 162 (46%) Bonferroni-significant CSF pQTLs were non-significant in plasma, indicating CSF-specific regulation.
- Mendelian randomization found 18 pQTL–protein pairs with shared genetic effects across 13 outcomes, including APOE, CD33, and GRN in AD; MMP10 in preclinical AD; SIGLEC9 in ALS; and CD38, GPNMB, and ADAM15 in PD. Observational CSF levels were altered for GRN in AD, MMP-10 in preclinical AD, and CD38 and GPNMB in PD.
- Ventricular volume was associated with 64 CSF proteins after FDR correction; adjusting for ventricular volume changed pQTL β-coefficients by up to 14%, and rs71635338 was associated with 1.51 SD larger ventricle volume (P = 0.007).
Methods
- Prospective BioFINDER cohort study of 1,591 participants (53% female; mean age 71.3 years) with CSF and plasma proteomics, mostly proximity extension assays (PEA), plus orthogonal assays; 398 CSF proteins and 368 plasma proteins were analyzed.
- Genome-wide pQTL analysis used 10.53 million common variants, linear regression adjusted for age, sex, diagnostic group, collection site, and sampling-to-assay time, with rank-based inverse-normal transformed residuals and Bonferroni correction (P < 1.253 × 10−10 for CSF).
- Mendelian randomization used cis-pQTL instruments with external GWAS summary data for 32 outcomes, and colocalization was tested with the coloc package; ventricular volume analyses used MRI data from a subset of 720 participants.
Limitations
- The paper states the cohort was elderly, limiting generalizability to younger populations; PEA antibody binding could be affected by missense variants, potentially producing erroneous pQTLs, especially for APOE, SIGLEC9, and FLRT2; and the study covered only ~400 proteins, about 2% of the proteome.
- The authors also state that lack of post-mortem brain tissue limited protein quantification to CSF and plasma, that genetic association does not necessarily reveal functional consequence, and that whole-exome or whole-genome sequencing is recommended for future work.
- Evident from the text: ventricular volume confounded several CSF pQTLs, and although most findings remained significant after adjustment, some were attenuated, so residual confounding or dilution effects may affect other CSF pQTL studies.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
35 of 43 cited sources checked · 24 supported · 0 flagged · accuracy not yet measured
- Findingown data
Eight cis pQTL-protein pairs had a proxy match (up to 10 kb) with Yang et al (2021) pQTL-protein pairs.
“Further, we identified 8 cis pQTL‐protein pairs with a proxy match (up to 10 kb) with Yang et al (2021) pQTL‐protein pairs (with the same protein and same directionality in the two studies).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Yang et al, 2021 source
- Premisecitation
Only a few genetic studies of the CSF proteome have been performed to date on larger sets of proteins.
“only a few such studies have been performed to date on larger sets of proteins (Kunkle et al, 2019; Sasayama et al, 2019; Yang et al, 2021)”
Quote in the paperSubstantial claim2 of 3 sources checked- cites Kunkle et al, 2019 source
The Results section on candidate gene prioritization discusses Alzheimer’s disease risk loci and brain gene-expression data, not genetic studies of the CSF proteome. Searches for “CSF,” “cerebrospinal fluid proteins,” and larger protein sets found no passage establishing either that this paper is such a study or that only a few such studies existed. The cited paper therefore does not verify this claim in our copy. (LLM, conf=0.74)
Experimental — accuracy not yet measured - cites Sasayama et al, 2019 source
- cites Yang et al, 2021 source
- Findingown data
53 of the cis-pQTLs identified in this study showed previous evidence of association with gene expression in brain tissues.
“When comparing with the eQTL meta‐analysis study, 53 of the cis‐pQTLs identified in the current study showed previous evidence of association with gene expression in brain tissues.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Sieberts et al, 2020 source
- Findingcitation
The overall genetic architecture of the CSF pQTLs was similar to findings reported for plasma pQTLs, gene expression QTLs, and a recent study on CSF pQTLs.
“The overall genetic architecture of the CSF pQTLs was similar to findings reported for plasma pQTLs (Sun et al, 2018), gene expression QTLs (Stranger et al, 2012), and a recent study on CSF pQTLs (Yang et al, 2021).”
Quote in the paperNot a substantial claim3 of 3 sources checked - Findingcitation
The causal association between CD33 (also known as Siglec-3) and AD was replicated between this study and Yang et al (2021).
“Among our gene‐level findings, the causal association between CD33 (also known as Siglec‐3) and AD was replicated between the studies.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Yang et al, 2021 source
- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Premisecitation
A recent large-scale study directly compared the aptamer-based SomaScan technology with antibody-based PEA and found considerable differences in results.
“A recent large‐scale study directly compared the aptamer‐based SomaScan technology with antibody‐based PEA and found considerable differences in results (Katz et al, 2022), which is in accordance with our findings.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Katz et al, 2022 source
- Study design and conductcitation
Most proteins were measured using validated, highly sensitive and specific PEA developed by Olink Proteomics.
“Most proteins were measured using validated, highly sensitive and specific PEA developed by Olink Proteomics (Uppsala, Sweden) as described before (Whelan et al, 2019).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Whelan et al, 2019 source
- Premisecitation
Mass spectrometry-based methods may be less susceptible to this type of artifact.
“Mass spectrometry‐based methods, which simultaneously measure across multiple peptides per protein, may be less susceptible to this type of artifact (Solomon et al, 2018), and were used in this study for quantification of certain proteins (Dataset EV1).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Solomon et al, 2018 source
- Findingown data
The APOE pQTL (rs429358) had shared effects with AD, preclinical AD, amygdala volume, hippocampus volume, and nucleus accumbens volume.
“The APOE pQTL (rs429358) had shared effects with AD, preclinical AD, amygdala volume, hippocampus volume, and nucleus accumbens volume.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Findingown data
The MMP10 pQTL (rs11225415) had shared effects with preclinical AD.
“The MMP10 pQTL (rs11225415) had shared effects with preclinical AD.”
Quote in the paperNot a substantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Findingown data
Ventricular volume measured with brain MRI was a confounder for several pQTLs.
“Ventricular volume (measured with brain magnetic resonance imaging) was a confounder for several pQTLs.”
Quote in the paperSubstantial claim - Findingown data
The SIGLEC9 pQTL (rs2258983) had shared effects with amyotrophic lateral sclerosis.
“The SIGLEC9 pQTL (rs2258983) had shared effects with amyotrophic lateral sclerosis.”
Quote in the paperNot a substantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Findingown data
The EBI GWAS catalog query found 77 hits, including 42 unique genetic variants, for variants mapped to GMNC or OSTN.
“There were 77 hits in total (Dataset EV13), including 42 unique genetic variants.”
Quote in the paperSubstantial claim - Findingown data
The overall replication rate between the studies was quite low.
“The overall replication rate between the studies was therefore quite low.”
Quote in the paperSubstantial claim - Findingnone given
Several other proteins were uniquely implicated in this study versus Yang et al (2021).
“We note that another recent CSF pQTL study also implicated CD33 for AD by MR analysis (Yang et al, 2021), while several other proteins were uniquely implicated in this study versus in Yang et al (2021).”
Quote in the paperNot a substantial claim - Findingown data
The GMNC-OSTN region was implicated in 19 of the 20 CSF pQTLs with the largest reductions in β-coefficients following ventricle adjustment.
“For example, this region was implicated in 19 of the 20 CSF pQTLs with largest reductions in β‐coefficients following ventricle adjustment, further implicating this genomic region in the interplay between genetic regulation, brain anatomy, and the CSF proteome.”
Quote in the paperSubstantial claim - Findingown data
A genomic region on chromosome 3, shown before to be related to brain morphology, was implicated for several CSF-specific pQTLs.
“A genomic region on chromosome 3, shown before to be related to brain morphology, was implicated for several CSF‐specific pQTLs.”
Quote in the paperNot a substantial claim - Findingown data
The strengths of the associations for cis-pQTL decreased at longer distance from transcription start sites.
“the strengths of the associations for cis‐pQTL decreased at longer distance from transcription start sites (Fig 3B).”
Quote in the paperNot a substantial claim - Findingown data
197 plasma pQTLs were found, including 141 cis-pQTLs and 56 trans-pQTLs, among 153 proteins.
“We also found 197 plasma pQTLs (N = 141 cis‐pQTLs and N = 56 trans‐pQTLs), among 153 proteins.”
Quote in the paperNot a substantial claim - Findingown data
CSF levels of GPNMB were altered in Parkinson's disease.
“CSF levels of GRN, MMP‐10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively.”
- Also stated in: § Shared genetic effects between pQTLs and neuropsychiatric traits · plain
“We found significant effects for GRN in AD, for MMP‐10 in preclinical AD, and for CD38 and GPNMB in PD, supporting the MR findings (Table EV2).”
Quote in the paperSubstantial claim - Also stated in: § Shared genetic effects between pQTLs and neuropsychiatric traits · plain
- Findingown data
Drug candidates were available for APOE, CD33, GRN, CD38, ADAM15, and CTSS.
“We queried the Cortellis Integrity database for cis‐pQTL proteins identified in the MR analyses and found that drug candidates were available for APOE, CD33, GRN, CD38, ADAM15, and CTSS (Table 2).”
Quote in the paperSubstantial claim - Findingown data
After FDR-correction, 64 CSF proteins were associated with ventricular volume.
“After FDR‐correction, 64 CSF proteins were associated with ventricular volume (Fig 6A).”
Quote in the paperSubstantial claim - Findingown data
Several CSF pQTLs correlated with gene expression in the brain.
“Comparisons against previously published eQTLs showed that several CSF pQTLs correlated with gene expression in the brain, supporting their biological relevance.”
Quote in the paperSubstantial claim - Findingown data
Eight genetic variants had significant trans-pQTLs (N = 36 in total) in a region on chromosome 3 where the closest encoding gene downstream was GMNC and the closest encoding gene upstream was OSTN.
“Eight genetic variants had significant trans‐pQTLs (N = 36 in total, Dataset EV12) in a region where the closest encoding gene downstream was GMNC (Ensembl gene ID ENSG00000205835) and the closest encoding gene upstream was OSTN (Ensembl gene ID ENSG00000188729).”
Quote in the paperSubstantial claim - Findingown data
The CD33 pQTL (rs273634) and GRN pQTL (rs5848) had shared effects with AD.
“The CD33 pQTL (rs273634) and GRN pQTL (rs5848) had shared effects with AD.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Findingnone given
The study identified ventricular volume as a possible confounder for CSF pQTL studies.
“We also identified ventricular volume as a possible confounder for CSF pQTL studies.”
Quote in the paperNot a substantial claim - Findingown data
A direct comparison showed that 15 pQTLs were exactly replicated between the studies, with the same variant and protein and the same direction of effect size with respect to risk allele.
“A direct comparison between the results showed that 15 pQTLs were exactly replicated between the studies (the same variant and protein and with the same direction of effect size with respect to risk allele).”
Quote in the paperSubstantial claim - Findingown data
Several CSF protein-pQTL pairs with effects of adjustment from ventricular volume involved the GMNC-OSTN region on chromosome 3.
“In particular, we noted that several CSF protein‐pQTL pairs with effects of adjustment from ventricular volume involved the GMNC‐OSTN region on chromosome 3.”
Quote in the paperSubstantial claim - Findingown data
Three different pQTL-protein pairs had shared effects with PD, including CD38-rs4266290, GPNMB-rs199348, and ADAM15-rs3806256.
“Three different pQTL‐protein pairs had shared effects with PD, including CD38‐rs4266290, GPNMB‐rs199348, and ADAM15‐rs3806256.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Findingown data
The study identified 176 significant (after Bonferroni correction) protein quantitative trait loci (pQTL) associated with altered CSF protein levels.
“We identified 176 significant (after Bonferroni correction) protein quantitative trait loci (pQTL), which were associated with altered CSF protein levels.”
Quote in the paperSubstantial claim - Findingown data
The study identified several genetic variants that were associated with protein levels in the CSF.
“We identified several genetic variants that were associated with protein levels in the CSF, which may have implications for protein regulation in the central nervous system.”
Quote in the paperSubstantial claim - Findingown data
RARRES2-rs3735172 had a posterior probability of 0.82 with years of schooling.
“RARRES2‐rs3735172 had a posterior probability of 0.82 with years of schooling.”
Quote in the paperNot a substantial claim - Findingown data
The minor allele frequencies of the pQTLs were inversely correlated with effect size.
“The minor allele frequencies of the pQTLs were inversely correlated with effect size (Fig 3A)”
Quote in the paperNot a substantial claim - Findingown data
Variant rs429358 was associated with multiple CSF proteins (6 trans-pQTLs and 1 cis-pQTL).
“We noted that the variant rs429358 was associated with multiple CSF proteins (N = 6 trans‐pQTLs and N = 1 cis‐pQTLs).”
Quote in the paperNot a substantial claim - Findingown data
pQTLs for CSF and plasma proteins were overall correlated.
“pQTLs for CSF and plasma proteins were overall correlated, but CSF‐specific pQTLs were also observed.”
- Also stated in: § Genome‐wide analysis of 398 CSF proteins reveals 176 independent genetic loci associated with CSF levels of 145 proteins · plain
“In general, CSF and plasma pQTL were highly correlated (Spearman Rho = 0.69, P < 0.001, Fig EV3).”
Quote in the paperNot a substantial claim - Also stated in: § Genome‐wide analysis of 398 CSF proteins reveals 176 independent genetic loci associated with CSF levels of 145 proteins · plain
- Findingown data
Seven CSF trans-pQTLs reached the a priori interaction score limit > 0.7, indicating previous evidence of significant gene-to-gene links.
“Seven of the CSF trans‐pQTLs reached the a priori determined interaction score limit (> 0.7), indicating previous evidence of significant gene‐to‐gene links.”
Quote in the paperNot a substantial claim - Findingown data
Among genes with putative CSF-specific pQTLs, two genes were enriched in cerebral cortex: OSTN (N = 34 trans-pQTLs) and DRAXIN (N = 1 cis-pQTL).
“When testing for tissue enrichment among the genes with putative CSF‐specific pQTLs, two genes were enriched in cerebral cortex (OSTN, N = 34 trans‐pQTLs and DRAXIN, N = 1 cis‐pQTL).”
Quote in the paperNot a substantial claim - Findingown data
CSF levels of MMP-10 were altered in preclinical Alzheimer's disease.
“CSF levels of GRN, MMP‐10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively.”
- Also stated in: § Shared genetic effects between pQTLs and neuropsychiatric traits · plain
“We found significant effects for GRN in AD, for MMP‐10 in preclinical AD, and for CD38 and GPNMB in PD, supporting the MR findings (Table EV2).”
Quote in the paperSubstantial claim - Also stated in: § Shared genetic effects between pQTLs and neuropsychiatric traits · plain
- Findingown data
The colocalization posterior probability for GPNMB-rs199348 with PD was 0.93.
“The colocalization posterior probability for GPNMB‐rs199348 with PD was 0.93.”
Quote in the paperSubstantial claim - Findingown data
176 pQTLs for 145 CSF proteins were identified at P < 1.25 × 10−10, including 117 cis-pQTLs and 59 trans-pQTLs.
“Protein quantitative trait loci (pQTL) were identified as associations between genetic variants and proteins, with 176 pQTLs for 145 CSF proteins (P < 1.25 × 10−10, 117 cis‐pQTLs and 59 trans‐pQTLs).”
- Also stated in: § Genome‐wide analysis of 398 CSF proteins reveals 176 independent genetic loci associated with CSF levels of 145 proteins · plain
“we found 176 significant CSF pQTLs among 145 proteins (Figs 2 and EV1), including cis‐pQTLs (N = 117) and trans‐pQTLs (N = 59).”
Quote in the paperSubstantial claim - Also stated in: § Genome‐wide analysis of 398 CSF proteins reveals 176 independent genetic loci associated with CSF levels of 145 proteins · plain
- Findingown data
After Bonferroni correction, there were 18 pQTL-protein pairs with strong WR evidence for sharing a genetic effect across 13 different outcomes.
“After Bonferroni correction (over the entire set of MR analyses), there were 18 pQTL‐protein pairs with strong WR evidence for sharing a genetic effect across 13 different outcomes.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Findingown data
Out of 162 Bonferroni significant CSF pQTLs where the matching protein was also analyzed in plasma, 74 (46%) were non-significant even at genome-wide level in plasma.
“out of 162 Bonferroni significant CSF pQTLs where the matching protein was also analyzed in plasma, there were 74 (46%) pQTLs (44 cis‐pQTLs and 43 trans‐pQTLs, distributed among 39 putative genes) which were non‐significant even at genome‐wide level (P > 5 × 10−8) in plasma.”
Quote in the paperSubstantial claim - Findingown data
rs71635338 was associated with ventricle volume (β = 1.51 standard deviations larger ventricle volume for the minor allele compared to the reference allele, P = 0.007), adjusting for intracranial volume, age, sex, diagnostic group, and the top 10 principal components.
“The analysis confirmed our hypothesis that this SNP (like other previously described SNPs in the GMNC‐OSTN region) was associated with ventricle volume (β = 1.51 standard deviations larger ventricle volume for the minor allele compared to the reference allele, P = 0.007).”
Quote in the paperSubstantial claim - Findingown data
MR analyses on cis-pQTL findings identified CSF proteins implicated in AD, PD, ALS, depression, bipolar disease, epilepsy, and brain volume measures.
“Using MR analyses on cis‐pQTL findings, we identified CSF proteins that were implicated in different neurological diseases, including AD, PD, ALS, depression, bipolar disease, and epilepsy, as well as brain volume measures.”
Quote in the paperSubstantial claim - Findingown data
Variant rs71635338 was significantly associated with 24 different CSF proteins (all trans-pQTLs).
“One notable exception was the genomic region represented by variant rs71635338 which was significantly associated with 24 different CSF proteins (all trans‐pQTLs).”
Quote in the paperNot a substantial claim - Findingown data
In Mendelian randomization experiments, the study identified proteins with shared genetic effects with several brain diseases, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and others.
“In Mendelian randomization experiments, which also leveraged genetic risk data for traits related to brain diseases, we identified proteins with shared genetic effects with several diseases, including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and others.”
Quote in the paperSubstantial claim- The authors state this as an assumption: SUVRs have a linear association with allele frequency.
- Findingown data
Out of the 18 pQTL-protein pairs, six pQTLs showed colocalization with eight different outcomes at a posterior probability > 0.75.
“Out of the 18 pQTL‐protein pairs we found six pQTLs showing colocalization with eight different outcomes at a posterior probability > 0.75.”
Quote in the paperSubstantial claim - Findingown data
Variants in the GMNC-OSTN region were common among the CSF pQTLs where ventricular volume had large confounding effects.
“We noted that variants in the GMNC‐OSTN region were common among the CSF pQTLs where ventricular volume had large confounding effects (Fig EV5).”
Quote in the paperSubstantial claim - Findingown data
CSF levels of GRN were altered in Alzheimer's disease.
“CSF levels of GRN, MMP‐10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively.”
- Also stated in: § Shared genetic effects between pQTLs and neuropsychiatric traits · plain
“We found significant effects for GRN in AD, for MMP‐10 in preclinical AD, and for CD38 and GPNMB in PD, supporting the MR findings (Table EV2).”
Quote in the paperSubstantial claim - Also stated in: § Shared genetic effects between pQTLs and neuropsychiatric traits · plain
- Findingown data
The SIGLEC9-rs2258983 protein-pQTL association had a posterior probability of 0.93 with ALS.
“The SIGLEC9‐rs2258983 protein‐pQTL association had a posterior probability of 0.93 with ALS.”
Quote in the paperSubstantial claim - Findingown data
Two protein-pQTL pairs (FLRT2-rs17646457 and RARRES2-rs3735172) had shared effects with focal epilepsy, as well as hippocampal sclerosis-related epilepsy.
“We also observed two protein‐pQTL pairs (FLRT2‐rs17646457 and RARRES2‐rs3735172) with shared effects with focal epilepsy, as well as hippocampal sclerosis‐related epilepsy.”
Quote in the paperNot a substantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Findingown data
Most genetic variants among the significant pQTLs were only associated with one CSF protein.
“Conversely, most genetic variants among the significant pQTLs were only associated with one CSF protein (Fig 4B).”
Quote in the paperNot a substantial claim - Findingown data
Most of the findings for CSF pQTLs were completely or partly novel.
“As shown in our detailed EBI GWAS query, most of the findings for CSF pQTLs were completely or partly novel.”
Quote in the paperSubstantial claim - Findingown data
Several genetic variants and CSF proteins were associated with volumes of the cerebral ventricles.
“In a novel approach which integrated volumetric MRI, we found that several genetic variants and CSF proteins were associated with volumes of the cerebral ventricles.”
Quote in the paperSubstantial claim - Findingown data
Several CSF proteins identified in the MR analysis for AD (GRN), preclinical AD (MMP-10), and PD (CD38 and GMBP) were also validated with observational differences between patients and controls.
“Several CSF proteins identified in the MR analysis for AD (GRN), preclinical AD (MMP‐10), and PD (CD38 and GMBP) were also validated with observational differences between patients and controls.”
Quote in the paperSubstantial claim - Findingown data
CSF-specific pQTLs were observed.
“pQTLs for CSF and plasma proteins were overall correlated, but CSF‐specific pQTLs were also observed.”
- Also stated in: § Genome‐wide analysis of 398 CSF proteins reveals 176 independent genetic loci associated with CSF levels of 145 proteins · plain
“out of 162 Bonferroni significant CSF pQTLs where the matching protein was also analyzed in plasma, there were 74 (46%) pQTLs (44 cis‐pQTLs and 43 trans‐pQTLs, distributed among 39 putative genes) which were non‐significant even at genome‐wide level (P > 5 × 10−8) in plasma.”
Quote in the paperSubstantial claim - Also stated in: § Genome‐wide analysis of 398 CSF proteins reveals 176 independent genetic loci associated with CSF levels of 145 proteins · plain
- Findingown data
IL-6 has a cis-pQTL (rs79103996) that was highly significant in CSF (P = 2.9 × 10−29) but had no association in plasma (P = 0.38).
“One example was IL‐6, with a cis‐pQTL (rs79103996) that was highly significant in CSF (P = 2.9 × 10−29) but had no association in plasma (P = 0.38)”
Quote in the paperSubstantial claim - Interpretationown data
New possible treatment targets for several neurological diseases were nominated.
“New possible treatment targets for several neurological diseases were nominated.”
Quote in the paperSubstantial claim - Interpretationown data
Mendelian randomization analyses suggested a causal role for GRN in Alzheimer's disease.
“Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Interpretationown data
Some proteins have distinct genetic regulation within the central nervous system that is different from that in the periphery.
“Comparisons against plasma pQTLs on the same subjects support that some proteins have distinct genetic regulation within the central nervous system that is different from that in the periphery.”
Quote in the paperSubstantial claim - Study design and conductnone given
Due to lack of availability of post-mortem brain tissue, the study was limited to protein quantification in CSF and blood plasma.
“Due to lack of availability of post‐mortem brain tissue, our study was limited to protein quantification in CSF and blood plasma.”
Quote in the paperSubstantial claim - Study design and conductown data
For three proteins with significant CSF pQTL findings, the pQTL findings were validated using alternative assays.
“For three proteins with significant CSF pQTL findings, we had measures with both PEA and additional assays (Meso Scale Discovery for CCL2 and CCL4, and ELISA for CHI3L1), and the pQTL findings were validated using the alternative assays (Fig EV2; Dataset EV2, lines marked in yellow).”
Quote in the paperNot a substantial claim - Interpretationown data
Mendelian randomization analyses suggested a causal role for CD38 in Parkinson's disease.
“Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Interpretationown data
The IL-6 cis-pQTL finding suggests relevant tissue-specificity of IL-6 regulation.
“suggesting relevant tissue‐specificity of IL‐6 regulation.”
Quote in the paperSubstantial claim - Interpretationown data
The GMNC-OSTN region is implicated in the interplay between genetic regulation, brain anatomy, and the CSF proteome.
“For example, this region was implicated in 19 of the 20 CSF pQTLs with largest reductions in β‐coefficients following ventricle adjustment, further implicating this genomic region in the interplay between genetic regulation, brain anatomy, and the CSF proteome.”
Quote in the paperSubstantial claim - Interpretationreasoning
The cohort consisted of elderly people, which limits the generalizability of the results to younger populations.
“Our cohort consisted of elderly people, which limits the generalizability of the results to younger populations.”
Quote in the paperNot a substantial claim - Interpretationown data
Mendelian randomization analyses suggested a causal role for GPNMB in Parkinson's disease.
“Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Interpretationown data
Mendelian randomization analyses suggested a causal role for MMP-10 in preclinical Alzheimer's disease.
“Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Interpretationreasoning
The GMNC-OSTN genomic region is relevant for CNS-related molecular pathways.
“Twenty out of 29 unique reported traits were brain‐related, mainly comprising volumetric brain measures, including of ventricle volume or white matter lesions, supporting the relevance of this genomic region for CNS‐related molecular pathways.”
Quote in the paperSubstantial claim - Interpretationown data
Mendelian randomization analyses suggested a causal role for ADAM15 in Parkinson's disease.
“Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Study design and conductown data
Annotation through chromatin interaction analysis yielded largely overlapping results with genomic distance annotation.
“Our main method to annotate pQTL genes was by genomic distance, but annotation through chromatin interaction analysis yielded largely overlapping results (Dataset EV2).”
Quote in the paperNot a substantial claim - Interpretationreasoning
OSTN is a possible causal gene for the CSF trans-pQTLs in the GMNC-OSTN region.
“Based on this, we suggest that OSTN is a possible causal gene for the CSF trans‐pQTLs in this region.”
Quote in the paperSubstantial claim- Rests on an assumption: GMNC has only weak expression in brain.
- Interpretationown data
CSF proteins associated with ventricle volume are likely to originate from the brain.
“This supported our hypothesis that CSF proteins associated with ventricle volume are likely to originate from the brain.”
Quote in the paperSubstantial claim - Interpretationown data
Mendelian randomization analyses suggested a causal role for SIGLEC9 in amyotrophic lateral sclerosis.
“Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Interpretationown data
The association described by Jansen et al (2022) may have been confounded by genetic effects on brain anatomy, causing differences in dilution and concentration across a range of CSF biomarkers.
“However, the findings in our current study suggest that the association described by Jansen et al (2022) may have been confounded by the genetic effects on brain anatomy, causing differences in dilution and concentration across a range of CSF biomarkers.”
Quote in the paperSubstantial claim - Interpretationown data
Ventricle volume is a confounder for some CSF pQTL analyses.
“These results support ventricle volume as a confounder for some CSF pQTL analyses.”
Quote in the paperSubstantial claim- Rests on an assumption: The MRI subset is representative of the full cohort for analyses of ventricle volume and CSF pQTL confounding.
- Study design and conductown data
In a sensitivity analysis, repeating the CSF analyses in cognitively normal controls gave similar results as the main analysis.
“in a sensitivity analysis, we repeated the CSF analyses in the subgroup of cognitively normal controls, with similar results as the main analysis (Appendix Fig S2).”
Quote in the paperNot a substantial claim - Interpretationown data
Mendelian randomization analyses suggested a causal role for ApoE in Alzheimer's disease.
“Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- Interpretationnone given
CSF pQTLs may be susceptible to confounding effects of brain ventricular volume.
“We also demonstrate that CSF pQTLs may be susceptible to confounding effects of brain ventricular volume.”
Quote in the paperSubstantial claim - Interpretationown data
Mendelian randomization analyses suggested a causal role for CD33 in Alzheimer's disease.
“Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
- May combine two claims. 47
- Classified as probably not a substantial claim. 38
May combine two claims.
FindingcitationAPOE genotype was associated with lower Aβ42 and higher T-tau and P-tau in CSF, validating known associations with Alzheimer's disease biomarkers.
“This genetic variant defines the APOE genotype, which has well‐known associations with CSF biomarkers related to Alzheimer's disease (AD), which were validated here (lower Aβ42, higher T‐tau and P‐tau (Chung et al, 2018)).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Chung et al, 2018 source
The Results (§3.1) and Discussion (§4; page unavailable) report APOE ε4 associations with CSF Aβ42, total tau, and phosphorylated tau in people with mild cognitive impairment. They do not state the claimed directions—lower Aβ42 and higher tau—and the Discussion says APOE ε4 was not associated with CSF tau biomarkers in cognitively normal subjects. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationCSF and plasma samples were collected and analyzed following a standardized protocol.
“CSF and plasma samples were collected and analyzed following a standardized protocol (Palmqvist et al, 2017).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Palmqvist et al, 2017 source
The Methods sections on CSF biomarkers and the BioFINDER study describe CSF sampling and specify the assays used to analyze CSF biomarkers (page numbers unavailable). They do not describe plasma sample collection or analysis, or establish that both sample types followed a standardized protocol. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe specificity of aptamer-based multiplex methods has been discussed before.
“The specificity of aptamer‐based multiplex methods has also been discussed before (Christiansson et al, 2014; Joshi & Mayr, 2018).”
Quote in the paperNot a substantial claim2 of 2 sources checkedClassified as probably not a substantial claim. May combine two claims.
PremisecitationGenetic variants in the GMNC-OSTN region on chromosome 3 were associated both with smaller ventricles and with increased CSF levels of the AD biomarker P-tau.
“Recently, it was reported that genetic variants in the GMNC‐OSTN region on chromosome 3 (described in detail in this study) were associated both with smaller ventricles and with increased CSF levels of the AD biomarker P‐tau (Jansen et al, 2022).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Jansen et al, 2022 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAnother recent CSF pQTL study also implicated CD33 for AD by MR analysis.
“We note that another recent CSF pQTL study also implicated CD33 for AD by MR analysis (Yang et al, 2021), while several other proteins were uniquely implicated in this study versus in Yang et al (2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Yang et al, 2021 source
The Results section (“Mendelian randomization and drug repositioning”; page unavailable) says MR implicated CD33 in AD, and the study did analyze CSF pQTLs. However, it identifies the CD33–AD result specifically as a plasma-protein finding, not a CSF CD33 finding. (LLM, conf=0.86)
Experimental — accuracy not yet measured
May combine two claims.
PremisecitationOSTN encodes osteocrin, a hormone that regulates dendritic growth in cerebral cortex, and has enhanced expression in the cerebral cortex.
“OSTN encodes a hormone (osteocrin) that regulates dendritic growth in cerebral cortex (Ataman et al, 2016), with enhanced expression in the cerebral cortex (according to The Human Protein Atlas).”
Quote in the paperSubstantial claim1 of 2 sources checked- cites Ataman et al, 2016 source
- cites The Human Protein Atlas
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationThe use of covariate adjustment in the pQTL analyses follows standard procedures.
“This use of covariate adjustment follows standard procedures (Folkersen et al, 2020) in pQTL analyses.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Folkersen et al, 2020 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationColocalization analysis used a strict Bayesian model with the coloc package in R.
“To estimate the prior likelihood of each genomic locus having a single variant affecting both the protein and the phenotype, we used a strict Bayesian model (colocalization analysis) using the coloc package in R (Giambartolomei et al, 2014).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Giambartolomei et al, 2014 source
May combine two claims.
PremisecitationYang et al (2021) described 226 CSF cis-pQTLs and 48 trans-pQTLs.
“Yang et al (2021) described 226 CSF cis‐pQTLs (at P < 5 × 10−8) and 48 trans‐pQTLs (at Bonferroni corrected P) compared to 158 CSF cis‐pQTLs (at P < 5 × 10−8) and 59 CSF trans‐pQTLs (at Bonferroni corrected P) in our study.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Yang et al, 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationSeveral members of the SIGLEC protein family have been implicated for roles in neurodegenerative diseases, especially due to neuroinflammatory properties.
“Regarding the MR findings of CD33 (SIGLEC‐3) in AD and SIGLEC‐9 in ALS, we note that several members of the SIGLEC protein family have been implicated for roles in neurodegenerative diseases, especially due to neuroinflammatory properties (Siddiqui et al, 2019).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Siddiqui et al, 2019 source
May combine two claims.
Findingown dataTwo pQTLs were common in both studies but associated with different proteins: rs76904798 was trans-acting and associated with GPNMB in this study and GRN in Yang et al (2021); rs12126142 was trans-acting in this study (PSME1) but cis-acting in Yang et al (2021) (IL6R).
“We also identified two additional pQTLs that were common in both studies but associated with different proteins. One of these (rs76904798) was trans‐acting and was associated with GPNMB in our study and GRN in Yang et al (2021). The second pQTL (rs12126142) was trans‐acting in our study (PSME1) but cis‐acting in the Yang et al (2021) study (IL6R).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Yang et al, 2021 source
Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
Classified as probably not a substantial claim.
PremisecitationPrevious studies have demonstrated associations between individual CSF biomarkers (Aβ, T-tau, and P-tau) and ventricle volume, likely dilution effects.
“Previous studies have demonstrated associations between individual CSF biomarkers (for the AD biomarkers Aβ, T‐tau, and P‐tau) and ventricle volume (likely dilution effects; Edsbagge et al, 2017; van Waalwijk van Doorn et al, 2017), but to our knowledge, this is the first large‐scale study of such associations, and how they affect associations between CSF biomarker and genetic variants.”
Quote in the paperSubstantial claim2 of 2 sources checked- cites Edsbagge et al, 2017 source
The Abstract and Aβ-related markers section report negative associations between ventricular CSF volume and Aβ38 and Aβ40. But the Discussion says T-tau and P-tau were not associated with measured CSF volumes and explicitly rejects mere dilution as the explanation for the Aβ associations. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites van Waalwijk van Doorn et al, 2017 source
The retrieved copy provides bibliographic details and keywords (no section or page), but no findings about associations of Aβ, T-tau, or P-tau with ventricular volume. Searches for those associations and for dilution effects returned no passage that addresses the claim. (LLM, conf=0.70)
Experimental — accuracy not yet measured
May combine two claims.
PremisecitationProximity extension assays have been shown to be sensitive and specific.
“We mainly used proximity extension assays (PEA), which have been shown to be sensitive and specific (Assarsson et al, 2014; Katz et al, 2022)”
Quote in the paperSubstantial claim2 of 2 sources checked- cites Assarsson et al, 2014 source
- cites Katz et al, 2022 source
The Discussion (page unavailable) reports evidence supporting the specificity of Olink’s proximity-extension-based measurements, including cis-pQTL associations and agreement with ELISA for four proteins. It does not establish generally high sensitivity: the authors say they could not independently determine detection limits, although the reagents in their ELISA validation quantified at least as low as the levels measured by ELISA. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationGPNMB is a transmembrane glycoprotein that has been studied before in cancer and inflammation.
“GPNMB (Glycoprotein nonmetastatic melanoma protein B) is a transmembrane glycoprotein, which has been studied before in cancer and inflammation (Saade et al, 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Saade et al, 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationSeveral studies in blood plasma have shown that pQTLs using aptamer-based and antibody-based assays are common and can explain up to 30% of protein variance.
“several studies in blood plasma have consistently shown that genetic variants associated with protein levels, known as protein quantitative trait loci (pQTL), using both aptamer‐based (Sun et al, 2018; Ferkingstad et al, 2021) and antibody‐based assays (Folkersen et al, 2020) are common and can explain up to 30% of the protein variance.”
Quote in the paperNot a substantial claim2 of 3 sources checked- cites Sun et al, 2018 source
The Methods (Protein measurements) describe the aptamer-based SOMAscan assay, and Genetic architecture of the plasma proteome reports 1,927 pQTLs, supporting the claim that such associations are common in plasma. That section reports a median of 5.8% of protein-level variation explained and more than 20% for 193 proteins, but does not establish the cited figure of up to 30%. The antibody-based studies are attributed to other citations in the sentence, not to Sun et al. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites Ferkingstad et al, 2021 source
- cites Folkersen et al, 2020 source
The Results section on genome-wide meta-analysis reports pQTLs for 85 of 90 plasma proteins, and Online Methods describes the antibody-based Olink assay. The Results section on heritability reports substantial variation explained by genetic scores, but our copy does not substantiate the specific claim that pQTLs explain up to 30% of protein variance; it gives different summary figures. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationFLRT2 has not been described extensively in relation to epilepsy or seizures, but there is evidence that this cell adhesion molecule is involved in neuronal development, including development of inhibitory cortical circuits.
“To our knowledge, FLRT2 (fibronectin leucine‐rich transmembrane protein 2) has not been described extensively in relation to epilepsy or seizures, but there is evidence that this cell adhesion molecule is involved in neuronal development, including development of inhibitory cortical circuits (Fleitas et al, 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Fleitas et al, 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationGPNMB's potential role in PD pathogenesis and links to aggregation of α-synuclein has recently been highlighted.
“Its potential role in PD pathogenesis and links to aggregation of α‐synuclein has recently been highlighted (Diaz‐Ortiz et al, 2022).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Diaz‐Ortiz et al, 2022 source
May combine two claims.
PremisecitationKatz et al (2022) found evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the PEA assays used in the current study.
“Importantly, Katz et al (2022) found evidence supporting more reliable protein target specificity and a higher number of phenotypic associations for the PEA assays, used in the current study.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Katz et al, 2022 source
May combine two claims.
Findingown dataFifteen pQTL-protein pairs were replicated between this study and Yang et al (2021) with significant effects and similar direction; 12 were cis-acting and 3 were trans-acting.
“Fifteen pQTL‐protein pairs were replicated (significant effects with similar direction of effect with respect to the risk allele) between the studies (see Fig EV4; Dataset EV7). Out of these 15, 12 pQTL‐protein pairs were cis‐acting and three were trans‐acting.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Yang et al, 2021 source
Split into 2 atoms — 1 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationPrevious studies found increased levels of CSF MMP-10 in AD, as well as increased rates of disease progression in those with high CSF MMP-10 levels at baseline.
“Regarding the role of MMP‐10 (matrix metalloproteinase 10) in preclinical AD, we note that previous studies found increased levels of CSF MMP‐10 in AD, as well as increased rates of disease progression in those with high CSF MMP‐10 levels at baseline (Martino Adami et al, 2022).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Martino Adami et al, 2022 source
May combine two claims.
Findingown dataCTSF was associated with one pQTL (rs572846) and had shared effects with bipolar disorder and depression.
“CTSF was associated with one pQTL (rs572846) and had shared effects with bipolar disorder and depression.”
Quote in the paperSubstantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
May combine two claims.
Findingown dataThe APOE pQTL (rs429358) had a colocalization posterior probability of 1 with AD, 0.81 with preclinical AD, 0.99 with amygdala volume, 0.87 with hippocampus volume and 0.95 with nucleus accumbens volume.
“The APOE pQTL (rs429358) had a colocalization posterior probability of 1 with AD, 0.81 with preclinical AD, 0.99 with amygdala volume, 0.87 with hippocampus volume and 0.95 with nucleus accumbens volume.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataWhen adjusting for ventricle volume and intracranial volume, pQTL β-coefficients changed by up to 14%, generally reduced, while P-values were generally increased.
“When adjusting for ventricle volume (and ICV), the β‐coefficients were changed by up to 14% (β‐coefficients were generally reduced, while P‐values were generally increased) (Fig EV5).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe pQTL-protein pairs CTSS-rs79671334 and RARRES2-rs3735172 had shared effects with schizophrenia and year of schooling, respectively.
“The pQTL‐protein pairs CTSS‐rs79671334 and RARRES2‐rs3735172 had shared effects with schizophrenia and year of schooling, respectively.”
Quote in the paperNot a substantial claim- Rests on an assumption: The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
May combine two claims.
Findingown dataIn a comparison between CSF pQTLs and brain eQTLs, there were both concordant associations, supporting direct links between gene transcription and translation, as well as discordant associations.
“In a comparison between CSF pQTLs and brain eQTLs, we noted that there were both concordant associations, supporting direct links between gene transcription and translation, as well as discordant associations.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataConcordant QTLs tended to have higher co-localization probability (18/35 had co-localization probability of at least 0.85), while discordant QTLs tended to have lower co-localization probability (only 4/18 had co-localization probability of at least 0.85).
“Co‐localization experiments showed that concordant QTLs tended to have higher co‐localization probability (18/35 had co‐localization probability of at least 0.85), while discordant QTLs tended to have lower co‐localization probability (only 4/18 had co‐localization probability of at least 0.85).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataMost CSF proteins had only one locus, predominantly acting in cis.
“Most CSF proteins had only one locus, predominantly acting in cis (Fig 4A, see Appendix Fig S3 for plasma pQTLs)”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataAlthough the study studied approximately 400 proteins, this is only approximately 2% of the proteome.
“Another limitation is that although we studied ~ 400 proteins, this is only ~ 2% of the proteome.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataTwenty out of 29 unique reported traits were brain-related, mainly comprising volumetric brain measures, including ventricle volume or white matter lesions.
“Twenty out of 29 unique reported traits were brain‐related, mainly comprising volumetric brain measures, including of ventricle volume or white matter lesions, supporting the relevance of this genomic region for CNS‐related molecular pathways.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThere were no plasma pQTLs in the GMNC-OSTN region, emphasizing its specificity for the CSF proteome in this study.
“There were no plasma pQTLs in this region, emphasizing its specificity for the CSF proteome in this study.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataNo altered levels were found for CD33 or APOE for AD, or ADAM15 for PD.
“We did not find altered levels for CD33 or APOE (for AD) or ADAM15 (for PD).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataCD33 pQTL (rs273634) and GRN pQTL (rs5848) had a posterior probability of 0.78 and 0.99, respectively, with AD.
“CD33 pQTL (rs273634) and GRN pQTL (rs5848) had a posterior probability of 0.78 and 0.99, respectively, with AD.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataSignificant observational differences between diagnostic groups were found for GRN in AD, MMP-10 in preclinical AD, and CD38 and GPNMB in PD, supporting the MR findings.
“We found significant effects for GRN in AD, for MMP‐10 in preclinical AD, and for CD38 and GPNMB in PD, supporting the MR findings (Table EV2).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataOur study described 158 CSF cis-pQTLs and 59 CSF trans-pQTLs.
“Yang et al (2021) described 226 CSF cis‐pQTLs (at P < 5 × 10−8) and 48 trans‐pQTLs (at Bonferroni corrected P) compared to 158 CSF cis‐pQTLs (at P < 5 × 10−8) and 59 CSF trans‐pQTLs (at Bonferroni corrected P) in our study.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe GTEx eQTL database query identified 7 additional cis-pQTLs, with concordant direction for 5 and discordant for 2.
“The GTEx eQTL database query resulted in identification of 7 additional cis‐pQTLs (not found in the meta‐analysis study), where the effect direction was concordant for 5 and discordant for 2 pQTLs (Appendix Fig S4 and Dataset EV9).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataFunctional annotation of CSF variants found enrichment for intronic, exonic, and downstream variants, while intergenic and ncRNA-intronic variants were significantly less common.
“We performed functional annotation of the CSF variants (Fig 3C) and found enrichment (after Bonferroni correction over 11 categories) for intronic (49% for CSF variants vs. 36% in a reference panel), exonic (1.8% vs. 1.0%), and downstream (1.7% vs. 1.1%) variants, while intergenic (35% vs. 47%) and ncRNA‐intronic (8.9% vs. 11.5%) were significantly less common.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe effect direction was concordant for 35 and discordant for 18 of the pQTLs.
“The effect direction was concordant for 35 and discordant for 18 of the pQTLs (Fig 5; Dataset EV8).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe seven trans-pQTLs with interaction score > 0.7 included CSF Aβ42, P-tau, and T-tau (for APOE), CCL4 (for CCR2 and CCR9), IL12A (for IL12B), and TNFSF13B (for TNFRSF13C).
“These included CSF Aβ42, P‐tau, and T‐tau (for APOE), CCL4 (for CCR2 and CCR9), IL12A (for IL12B), and TNFSF13B (for TNFRSF13C; Appendix Fig S5).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataGenes for proteins that were associated with ventricle volume showed strong enrichment for the cerebral cortex, while the remaining proteins did not show enrichment for any brain region.
“Genes for proteins that were associated with ventricle volume showed strong enrichment for the cerebral cortex (Fig 6B), while the remaining proteins did not show enrichment for any brain region (Fig 6C).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataA few CSF proteins had several trans-acting loci, including six loci for CCL4, four for RBKS, and three each for CCL24, CTSS, and LRPAP1.
“a few proteins had several trans‐acting loci (for all identified loci, the strongest pQTL was nominated and carried on further in all analyses), including six loci for CSF CCL4 (two cis‐pQTLs and four trans‐pQTLs), four for CSF RBKS (all cis‐pQTLs), and three each for CSF CCL24 (all cis‐pQTLs), CTSS (all cis‐pQTLs), and LRPAP1 (all trans‐pQTLs).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataAmong all significant CSF pQTLs, there were 140 unique genetic loci and 145 unique proteins.
“Among all significant (after Bonferroni correction) CSF pQTLs, there were 140 unique genetic loci and 145 unique proteins.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThere was no significant variance in findings related to assay batches.
“There was no significant variance in findings related to assay batches.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductown dataSubject-level QC was conducted, including removal of sexual incompatibility between chip-inferred sex and self-reported sex, low call rates, and extreme heterozygosity.
“Subject‐level QC was conducted, including the removal of sexual incompatibility between chip‐inferred sex and self‐reported sex, low call rates (5% cut‐off), and extreme heterozygosity.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe laboratory staff analyzing samples were blinded to all data.
“The laboratory staff analyzing samples were blinded to all data.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductown data18F-florbetapir PET SUVRs were regressed on each genetic variant adjusting for age, sex, and the first five principal components of genetic background to account for population stratification.
“18F‐florbetapir PET SUVRs were regressed on each genetic variant separately, adjusting for age, sex, and the first five principal components of the genetic background to account for unmeasured population stratification.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningThe MR analysis may be affected by pseudo pQTLs or pQTLs driven by epitope effects, especially for APOE, SIGLEC9, and FLRT2, which were missense variants.
“We cannot exclude that the MR analysis may be affected by “pseudo pQTLs” or pQTLs driven by epitope effects, i.e., that the assay detects protein with missense variant differently (especially for APOE, SIGLEC9, and FLRT2, which were missense variants).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningThe genetic association to a protein does not necessarily give information about the actual functional consequence of a genetic variant.
“Furthermore, the genetic association to a protein does not necessarily give information about the actual functional consequence of a genetic variant (i.e., the variant might alter total expression, or expression of one particular isoform of the protein that is detected, but not others).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductreasoningThe rs71635338-ventricle volume test was a single test based on an a priori hypothesis, so correction for multiple comparisons was not applicable.
“Note that this was a single test, based on an a priori hypothesis, whereby correction for multiple comparisons was not applicable.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataAlthough some pQTLs can be robustly replicated across distinct proteomics methods, aptamer- and antibody-based technologies largely provide non-overlapping information.
“This suggests that although some pQTLs can be robustly replicated across distinct proteomics methods, aptamer‐ and antibody‐based technologies largely provide non‐overlapping information.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationCSF is produced within the brain and is a rich source for biomarkers that correlate with brain pathologies across different diseases.
“Cerebrospinal fluid (CSF) is produced within the brain and is a rich source for biomarkers that correlate with brain pathologies across different diseases (Hansson, 2021).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Hansson, 2021 source
Classified as probably not a substantial claim.
Study design and conductcitationThe genome-wide association analysis to identify pQTLs adjusted for genetic principal components to adjust for population stratification.
“The genome‐wide association analysis to identify pQTLs were performed using PLINK1.9 with adjustment for genetic principal components to adjust for population stratification.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationDiscordant associations between pQTLs and eQTLs have been reported to varying degrees before.
“Discordant associations between pQTLs and eQTLs have been reported to varying degrees before (preprint: Sun et al, 2022) and may hypothetically reflect biological pathways with negative feedback loops that regulate protein levels.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites preprint: Sun et al, 2022
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductown dataAll proteins passed quality control in all measured samples, except for BDNF and CCL22, which were removed from all analyses.
“All proteins passed quality control (QC) (with warnings indicated in < 20% of samples) in all measured samples, except for BDNF and CCL22, which were therefore removed from all analyses (note that these proteins were later highlighted by Olink Proteomics as having technical issues and were replaced with other proteins in subsequent versions of the assays).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenStandard QC steps were performed for SNP-level filter to ensure conformity with the reference panel used for imputation.
“Standard QC steps were performed for SNP‐level filter to ensure conformity with the reference panel used for imputation (strand continuity, names of the alleles, position and assignments for Ref/Alt).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductown dataThe pQTL analysis adjusted for age, gender, diagnostic group, collection site, and time from sampling to assay execution.
“For each protein, a linear regression analysis was performed with adjustments for age, gender, diagnostic group, collection site, and time from sampling to assay execution.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductnone givenMulti-allelic variants and SNPs with a data imputation score < 0.2 were excluded, genotype calls with a posterior likelihood < 0.9 were set to fail, SNPs with a genotyping rate > 0.9 were retained, and SNPs with MAF ≥ 1% were used for the analyses.
“Multi‐allelic variants and SNPs with a data imputation score < 0.2 were excluded as part of post‐imputation QC and genotype calls with a posterior likelihood < 0.9 were set to fail (i.e., hard‐called). SNPs with a genotyping rate > 0.9 were retained. SNPs with MAF ≥ 1% were used for the analyses.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenAll participants provided informed consent and the study conformed to the principles set out in the WMA Declaration of Helsinki and the Department of Health and Human Services Belmont Report.
“All participants provided informed consent and the study conformed to the principles set out in the WMA Declaration of Helsinki and the Department of Health and Human Services Belmont Report.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationRARRES2 has chemotactic properties during inflammatory responses, and serum RARRES2 levels were associated with severity of seizures in children with idiopathic epilepsy.
“RARRES2 (retinoic acid receptor responder protein 2, also known as chemerin) is described as having chemotactic properties during inflammatory responses and serum RARRES2 levels were associated with severity of seizures in children with idiopathic epilepsy (Elhady et al, 2018).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Elhady et al, 2018 source
Classified as probably not a substantial claim.
Study design and conductnone givenThe genome-wide analyses were adjusted for diagnostic group.
“The genome‐wide analyses were adjusted for diagnostic group”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationCTSF is a lysosomal protein involved in the pathogenesis of some types of neuronal ceroid lipofuscinosis.
“CTSF (cathepsin F), implicated here for depression and bipolar disease, is a lysosomal protein which is involved in the pathogensis of some types of neuronal ceroid lipofuscinosis (Smith et al, 2013).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Smith et al, 2013 source
May combine two claims.
Interpretationown dataVentricle volume is a possible confounder for many CSF pQTL studies, although most findings remain significant (but sometimes attenuated) after adjustment for ventricle volume.
“The results point to ventricle volume as a possible confounder for many CSF pQTL studies, although we demonstrate that most findings remain significant (but sometimes attenuated) after adjustment for ventricle volume.”
Quote in the paperSubstantial claim- Rests on an assumption: The MRI subset is representative of the full cohort for analyses of ventricle volume and CSF pQTL confounding.
Classified as probably not a substantial claim.
Study design and conductnone givenAssay batches were randomized with respect to covariates.
“Assay batches were randomized with respect to covariates.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe BioFINDER study was approved by the regional Ethical Review Board in Lund.
“The BioFINDER study was approved by the regional Ethical Review Board in Lund (2008/289, 2008/695, 2010/156, 2010/401, 2013/494).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone givenPrior to downstream analyses, the study checked and verified that there was no allelic heterogeneity or locus heterogeneity in the available GWAS summary statistics files.
“Prior to downstream analyses, we checked and verified that there was no allelic heterogeneity or locus heterogeneity in the available GWAS summary statistics files.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Premisenone givenIdentification of pQTLs makes it possible to test if proteins are likely to be causal for development of human diseases.
“Identification of pQTLs makes it possible to test if proteins are likely to be causal for development of human diseases (hence nominating them as candidate drug targets).”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductown dataGenetic data from the A4 study underwent quality control limiting to variants with call rate > 95%, minor allele frequency > 1%, and Hardy-Weinberg equilibrium P > 10−6, and excluding cryptic relatedness.
“Genetic data from A4 underwent a quality control process limiting to variants with a call rate > 95%, minor allele frequency > 1%, if cryptic relatedness was identified, or if out of Hardy–Weinberg equilibrium (P > 10−6).”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductown dataRelatedness among the samples was eliminated by removing one participant from each pair of close relatives (first or second degree).
“Relatedness among the samples was eliminated by removing one participant from each pair of close relatives (first or second degree) identified as π^ ≥ 0.0625.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Study design and conductnone givenMulti-dimensional scaling was done using PLINK2 to create principal components in genetic analyses to account for ancestry.
“Multi‐dimensional scaling was done using PLINK2 to create principal components in genetic analyses to account for ancestry.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationeQTL and disease-associated loci may have fundamental differences, contributing to different results with these approaches.
“As recently pointed out, eQTL and disease‐associated loci may have fundamental differences, contributing to different results with these approaches (preprint: Mostafavi et al, 2022).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites preprint: Mostafavi et al, 2022
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductnone givenThe non-Olink proteins all passed thresholds of being quantifiable and passing QC in at least 80% of measured samples.
“The non‐Olink proteins all passed thresholds of being quantifiable and passing QC in at least 80% of measured samples.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Ventricular volume had not been evaluated as a confounder for CSF pQTLs before this study.
“We also evaluated ventricular volume measured with magnetic resonance imaging (MRI) as a potential confounder (due to dilution effects) for CSF pQTLs, which to our knowledge had not been done before in CSF pQTL studies.”
The paper relies on this without support.
The genetic variants used as instruments in Mendelian randomization are valid instruments: they are associated with the protein, not associated with confounders, and affect the outcome only through the protein.
“For the MR, we performed Wald ratio (WR) tests based on the independent cis‐pQTL instruments available for each protein.”
The paper relies on this without support.
CSF protein levels reflect proteins expressed in the brain and subsequently secreted to CSF.
“The overarching aim of the study was to map and decipher clinically relevant genetic regulation of proteins expressed in the brain and subsequently secreted to the CSF, with a focus on brain diseases in general and neurological diseases in particular.”
The paper relies on this without support.
GMNC has only weak expression in brain.
“GMNC (geminin coiled‐coil domain‐containing protein‐1) is a regulator of DNA replication, with only weak expression in brain.”
The paper relies on this without support.
The MRI subset is representative of the full cohort for analyses of ventricle volume and CSF pQTL confounding.
“Note that these analyses were done on a subset of participants with MRI data.”
The paper relies on this without support.
Many brain diseases lack efficient disease-modifying treatments.
“Many brain diseases lack efficient disease‐modifying treatments.”
The paper relies on this without support.
Studies of the genetic regulation of CSF proteins can give clues to novel targetable biological pathways of brain diseases.
“Studies of the genetic regulation of cerebrospinal fluid (CSF) proteins can give clues to novel targetable biological pathways of brain diseases.”
The paper relies on this without support.
Only a few studies have combined genotyping data and CSF data on large sets of proteins, which is needed for this type of analysis.
“However, only a few studies have combined genotyping data and CSF data on large sets of proteins, which is needed for this type of analysis.”
The paper relies on this without support.
There is a lack of studies using sensitive and specific antibody-based methods, such as proximity extension assays, for a large number of proteins.
“There is especially a lack of studies using sensitive and specific antibody‐based methods, such as proximity extension assays, for a large number of proteins.”
The paper relies on this without support.
Most published pQTLs represent protein abundance from plasma or serum samples, and only a small number represent prior CSF pQTL studies.
“While most published pQTLs represent protein abundance from plasma or serum samples, a small number represent prior CSF pQTL studies.”
The authors state this as an assumption.
SUVRs have a linear association with allele frequency.
“SUVRs were modeled using ordinary least squares regression assuming a linear association with allele frequency.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
OSTN is highly expressed in human neurons, regulates dendritic growth in the human brain and is proposed as a candidate gene at this locus.
“We note that OSTN, the gene flanking the 3’ end of this region, is highly expressed in human neurons, regulates dendritic growth in the human brain and is proposed as a candidate gene at this locus17.”
From Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for Alzheimer’s disease (2024) · cites this paper as [17]
The Results section (‘The GMNC‐OSTN region and CSF trans‐pQTLs’; page unavailable) says OSTN has enhanced expression in the cerebral cortex, encodes a hormone that regulates dendritic growth there, and is a possible causal gene for the region’s CSF trans-pQTLs. It does not establish that OSTN is highly expressed specifically in human neurons; cortical expression is a less specific claim. (LLM, conf=0.86)
Experimental — accuracy not yet measuredThis dataset represents an expansion of previous CSF pQTL work in both sample size (n=3,506) and number of proteins (n=6,361).
“This dataset represents an expansion of previous CSF pQTL work10,16–19 in both sample size (n=3,506) and number of proteins (n=6,361).”
From Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for Alzheimer’s disease (2024) · cites this paper as [17]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
CSF-specific pQTL subtypes exceed the reported total
MajorThe reported 44 cis-pQTLs and 43 trans-pQTLs sum to 87, not 74. This changes the stated count of CSF pQTLs without a genome-wide-significant plasma association.
Reported 74 · recomputed 87
“there were 74 (46%) pQTLs (44 cis‐pQTLs and 43 trans‐pQTLs, distributed among 39 putative genes)”
Discussion names GMBP instead of GPNMB for Parkinson's disease
MinorThe discussion describes an observationally validated PD protein as GMBP, while the results identify that protein as GPNMB.
“Several CSF proteins identified in the MR analysis for AD (GRN), preclinical AD (MMP‐10), and PD (CD38 and GMBP) were also validated with observational differences between patients and controls.”
“We found significant effects for GRN in AD, for MMP‐10 in preclinical AD, and for CD38 and GPNMB in PD, supporting the MR findings (Table EV2).”
Drug-candidate table names CTCF instead of the MR protein CTSF
MinorTable 2 lists CTCF for depression and bipolar disorder, but Table 1 identifies CTSF as the protein associated with both outcomes.
“| CTCF | NA | | | | Depression, bipolar disorder |”
“CTSF was associated with one pQTL (rs572846) and had shared effects with bipolar disorder and depression.”
Cites
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915 · see citing works
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,380 · see citing works
The MR-Base platform supports systematic causal inference across the human phenome
Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., Laurin, C., Burgess, S., Bowden, J., Langdon, R., et al. (2018) · eLife · doi:10.7554/elife.34408 · Cited by 7,959 · see citing works
Self-citationDiagnosis and management of dementia with Lewy bodies: Third report of the DLB consortium
McKeith, I. G., Dickson, D. W., Lowe, J., Emre, M., O'Brien, J. T., Feldman, H., Cummings, J., Duda, J. E., Lippa, C., Perry, E. K., et al. (2005) · Neurology · doi:10.1212/01.wnl.0000187889.17253.b1 · Cited by 5,069 · see citing works
Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261 · see citing works
Functional mapping and annotation of genetic associations with FUMA
Watanabe, K., Taskesen, E., van Bochoven, A., & Posthuma, D. (2017) · Nature Communications · doi:10.1038/s41467-017-01261-5 · Cited by 4,083 · see citing works
Clinical diagnostic criteria for dementia associated with Parkinson’s disease
Emre, M., Aarsland, D., Brown, R., Burn, D. J., Duyckaerts, C., Mizuno, Y., Broe, G. A., Cummings, J., Dickson, D. W., Gauthier, S., et al. (2007) · Movement Disorders · doi:10.1002/mds.21507 · Cited by 3,027 · see citing works
Alzheimer Disease Genetics Consortium (ADGC), Kunkle, B. W., The European Alzheimer’s Disease Initiative (EADI), Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE), Genetic and Environmental Risk in AD/Defining Genetic, P. A. E. R. F. A. D. C. (., Grenier-Boley, B., Sims, R., Bis, J. C., Damotte, V., Naj, A. C., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0358-2 · Cited by 2,946 · see citing works
Diagnostic Criteria for Parkinson Disease
Gelb, D. J., Oliver, E., & Gilman, S. (1999) · Archives of Neurology · doi:10.1001/archneur.56.1.33 · Cited by 2,822 · see citing works
Litvan, I., Agid, Y., Calne, D., Campbell, G., Dubois, B., Duvoisin, R. C., Goetz, C. G., Golbe, L. I., Grafman, J., Growdon, J. H., et al. (1996) · Neurology · doi:10.1212/wnl.47.1.1 · Cited by 2,538 · see citing works
Genomic atlas of the human plasma proteome
Sun, B. B., Maranville, J. C., Peters, J. E., Stacey, D., Staley, J. R., Blackshaw, J., Burgess, S., Jiang, T., Paige, E., Surendran, P., et al. (2018) · Nature · doi:10.1038/s41586-018-0175-2 · Cited by 2,268 · see citing works
Assarsson, E., Lundberg, M., Holmquist, G., Björkesten, J., Bucht Thorsen, S., Ekman, D., Eriksson, A., Rennel Dickens, E., Ohlsson, S., Edfeldt, G., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0095192 · Cited by 1,874 · see citing works
Genetic regulation of the human plasma proteome in 54,306 UK Biobank participants
Sun, B. B., Chiou, J., Traylor, M., Benner, C., Hsu, Y.-H., Richardson, T. G., Surendran, P., Mahajan, A., Robins, C., Vasquez-Grinnell, S. G., et al. (2022) · doi:10.1101/2022.06.17.496443 · Cited by 1,833 · see citing works
Self-citationPlasma proteomic associations with genetics and health in the UK Biobank
Sun, B. B., Chiou, J., Traylor, M., Benner, C., Hsu, Y.-H., Richardson, T. G., Surendran, P., Mahajan, A., Robins, C., Vasquez-Grinnell, S. G., et al. (2023) · Nature · doi:10.1038/s41586-023-06592-6 · Cited by 1,740 · see citing works
Self-citationLarge-scale integration of the plasma proteome with genetics and disease
Ferkingstad, E., Sulem, P., Atlason, B. A., Sveinbjornsson, G., Magnusson, M. I., Styrmisdottir, E. L., Gunnarsdottir, K., Helgason, A., Oddsson, A., Halldorsson, B. V., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00978-w · Cited by 1,697 · see citing works
Biomarkers for neurodegenerative diseases
Hansson, O. (2021) · Nature Medicine · doi:10.1038/s41591-021-01382-x · Cited by 1,159 · see citing works
Self-citationA meta-analysis of genome-wide association studies identifies 17 new Parkinson's disease risk loci
Chang, D., Nalls, M. A., Hallgrímsdóttir, I. B., Hunkapiller, J., van der Brug, M., Cai, F., International Parkinson's Disease Genomics Consortium, 23andMe Research Team, Kerchner, G. A., Ayalon, G., et al. (2017) · Nature Genetics · doi:10.1038/ng.3955 · Cited by 1,112 · see citing works
Consensus statement on the diagnosis of multiple system atrophy
Gilman, S., Low, P. A., Quinn, N. P., Albanese, A., Ben‐Shlomo, Y., Fowler, C. J., Kaufmann, H., Klockgether, T., Lang, A. E., Lantos, P. L., et al. (1999) · Journal of the Neurological Sciences · doi:10.1016/s0022-510x(98)00304-9 · Cited by 915 · see citing works
Palmqvist, S., Schöll, M., Strandberg, O., Mattsson, N., Stomrud, E., Zetterberg, H., Blennow, K., Landau, S., Jagust, W., & Hansson, O. (2017) · Nature Communications · doi:10.1038/s41467-017-01150-x · Cited by 911 · see citing works
Self-citationGenomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals
Folkersen, L., Gustafsson, S., Wang, Q., Hansen, D. H., Hedman, Å. K., Schork, A., Page, K., Zhernakova, D. V., Wu, Y., Peters, J., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-00287-2 · Cited by 705 · see citing works
Self-citationGenome-Wide Analyses Identify KIF5A as a Novel ALS Gene
Nicolas, A., Kenna, K. P., Renton, A. E., Ticozzi, N., Faghri, F., Chia, R., Dominov, J. A., Kenna, B., Nalls, M. A., Keagle, P. J., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.02.027 · Cited by 670 · see citing works
Genome-wide enhancer maps link risk variants to disease genes
Nasser, J., Bergman, D. T., Fulco, C. P., Guckelberger, P., Doughty, B. R., Patwardhan, T. A., Jones, T. R., Nguyen, T. H., Ulirsch, J. C., Lekschas, F., et al. (2021) · Nature · doi:10.1038/s41586-021-03446-x · Cited by 669 · see citing works
Litvan, I., Hauw, J., Bartko, J. J., Lantos, P. L., Daniel, S. E., Horoupian, D. S., McKee, A. C., Dickson, D. W., Bancher, C., Tabaton, M., et al. (1996) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/00005072-199601000-00010 · Cited by 474 · see citing works
Hall, S., Öhrfelt, A., Constantinescu, R., Andreasson, U., Surova, Y., Bostrom, F., Nilsson, C., Widner, H., Decraemer, H., Nägga, K., et al. (2012) · Archives of Neurology · doi:10.1001/archneurol.2012.1654 · Cited by 473 · see citing works
Self-citationPatterns of Cis Regulatory Variation in Diverse Human Populations
Stranger, B. E., Montgomery, S. B., Dimas, A. S., Parts, L., Stegle, O., Ingle, C. E., Sekowska, M., Smith, G. D., Evans, D., Gutierrez-Arcelus, M., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002639 · Cited by 470 · see citing works
Frontotemporal dementia and its subtypes: a genome-wide association study
Ferrari, R., Hernandez, D. G., Nalls, M. A., Rohrer, J. D., Ramasamy, A., Kwok, J. B. J., Dobson-Stone, C., Brooks, W. S., Schofield, P. R., Halliday, G. M., et al. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70065-1 · Cited by 383 · see citing works
Genetic mapping of cell type specificity for complex traits
Watanabe, K., Mirkov, M. U., de Leeuw, C., van den Heuvel, M. P., & Posthuma, D. (2019) · Nature Communications · doi:10.1038/s41467-019-11181-1 · Cited by 323 · see citing works
Sieberts, S. K., Perumal, T. M., Carrasquillo, M. M., Allen, M., Reddy, J. S., Hoffman, G. E., Dang, K. K., Calley, J., Ebert, P. J., Eddy, J., et al. (2020) · Scientific Data · doi:10.1038/s41597-020-00642-8 · Cited by 318 · see citing works
Zhao, B., Luo, T., Li, T., Li, Y., Zhang, J., Shan, Y., Wang, X., Yang, L., Zhou, F., Zhu, Z., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0516-6 · Cited by 295 · see citing works
Yang, C., Farias, F. H. G., Ibanez, L., Suhy, A., Sadler, B., Fernandez, M. V., Wang, F., Bradley, J. L., Eiffert, B., Bahena, J. A., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00886-6 · Cited by 290 · see citing works
TissueEnrich: Tissue-specific gene enrichment analysis
Jain, A., & Tuteja, G. (2018) · Bioinform. · doi:10.1093/bioinformatics/bty890 · Cited by 268 · see citing works
Multiplex proteomics identifies novel CSF and plasma biomarkers of early Alzheimer’s disease
Whelan, C. D., Mattsson, N., Nagle, M. W., Vijayaraghavan, S., Hyde, C., Janelidze, S., Stomrud, E., Lee, J., Fitz, L., Samad, T. A., et al. (2019) · Acta Neuropathologica Communications · doi:10.1186/s40478-019-0795-2 · Cited by 262 · see citing works
Self-citation(ADNI), A. D. N. I., Deming, Y., The Alzheimer Disease Genetic Consortium (ADGC), Li, Z., Kapoor, M., Harari, O., Del-Aguila, J. L., Black, K., Carrell, D., Cai, Y., et al. (2017) · Acta Neuropathologica · doi:10.1007/s00401-017-1685-y · Cited by 231 · see citing works
Self-citationThe Role of GPNMB in Inflammation
Saade, M., Araujo de Souza, G., Scavone, C., & Kinoshita, P. F. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.674739 · Cited by 216 · see citing works
Katz, D. H., Robbins, J. M., Deng, S., Tahir, U. A., Bick, A. G., Pampana, A., Yu, Z., Ngo, D., Benson, M. D., Chen, Z.-Z., et al. (2022) · Science Advances · doi:10.1126/sciadv.abm5164 · Cited by 206 · see citing works
GPNMB confers risk for Parkinson’s disease through interaction with α-synuclein
Diaz-Ortiz, M. E., Seo, Y., Posavi, M., Carceles Cordon, M., Clark, E., Jain, N., Charan, R., Gallagher, M. D., Unger, T. L., Amari, N., et al. (2022) · Science · doi:10.1126/science.abk0637 · Cited by 158 · see citing works
In Aptamers They Trust: Caveats of the SOMAscan Biomarker Discovery Platform From SomaLogic
Joshi, A., & Mayr, M. (2018) · Circulation · doi:10.1161/circulationaha.118.036823 · Cited by 155 · see citing works
Evolution of Osteocrin as an activity-regulated factor in the primate brain
Ataman, B., Boulting, G. L., Harmin, D. A., Yang, M. G., Baker-Salisbury, M., Yap, E.-L., Malik, A. N., Mei, K., Rubin, A. A., Spiegel, I., et al. (2016) · Nature · doi:10.1038/nature20111 · Cited by 149 · see citing works
Genome-wide meta-analysis for Alzheimer’s disease cerebrospinal fluid biomarkers
Jansen, I. E., van der Lee, S. J., Gomez-Fonseca, D., de Rojas, I., Dalmasso, M. C., Grenier-Boley, B., Zettergren, A., Mishra, A., Ali, M., Andrade, V., et al. (2022) · Acta Neuropathologica · doi:10.1007/s00401-022-02454-z · Cited by 132 · see citing works
Self-citationCathepsin F mutations cause Type B Kufs disease, an adult-onset neuronal ceroid lipofuscinosis
Smith, K. R., Dahl, H.-H. M., Canafoglia, L., Andermann, E., Damiano, J., Morbin, M., Bruni, A. C., Giaccone, G., Cossette, P., Saftig, P., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/dds558 · Cited by 130 · see citing works
Stacey, D., Fauman, E. B., Ziemek, D., Sun, B. B., Harshfield, E. L., Wood, A., Butterworth, A. S., Suhre, K., & Paul, D. S. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky837 · Cited by 107 · see citing works
Self-citationSiglecs in Brain Function and Neurological Disorders
Siddiqui, S. S., Matar, R., Merheb, M., Hodeify, R., Vazhappilly, C. G., Marton, J., Shamsuddin, S. A., & Al Zouabi, H. (2019) · Cells · doi:10.3390/cells8101125 · Cited by 100 · see citing works
Limited overlap of eQTLs and GWAS hits due to systematic differences in discoveryPreprint
Mostafavi, H., Spence, J. P., Naqvi, S., & Pritchard, J. K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.07.491045 · Cited by 86 · see citing works
The A4 study: β ‐amyloid and cognition in 4432 cognitively unimpaired adults
Insel, P. S., Donohue, M., Sperling, R. A., Hansson, O., & Mattsson, N. (2020) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51048 · Cited by 81 · see citing works
Self-citationFauman, E. B., & Hyde, C. L. (2022) · BMC Bioinformatics · doi:10.1186/s12859-022-04706-x · Cited by 81 · see citing works
Self-citationGenome‐wide association study of Alzheimer's disease endophenotypes at prediagnosis stages
Chung, J., Wang, X., Maruyama, T., Ma, Y., Zhang, X., Mez, J., Sherva, R., Takeyama, H., Initiative, T. A. D. N., Lunetta, K. L., et al. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2017.11.006 · Cited by 67 · see citing works
Increased amyloidogenic APP processing in APOE ɛ4-negative individuals with cerebral β-amyloidosis
Mattsson, N., Insel, P. S., Palmqvist, S., Stomrud, E., van Westen, D., Minthon, L., Zetterberg, H., Blennow, K., & Hansson, O. (2016) · Nature Communications · doi:10.1038/ncomms10918 · Cited by 60 · see citing works
Self-citationVojinovic, D., Adams, H. H., Jian, X., Yang, Q., Smith, A. V., Bis, J. C., Teumer, A., Scholz, M., Armstrong, N. J., Hofer, E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-06234-w · Cited by 52 · see citing works
Matrix metalloproteinase 10 is linked to the risk of progression to dementia of the Alzheimer’s type
Martino Adami, P. V., Orellana, A., García, P., Kleineidam, L., Alarcón-Martín, E., Montrreal, L., Aguilera, N., Espinosa, A., Abdelnour, C., Rosende-Roca, M., et al. (2022) · Brain · doi:10.1093/brain/awac024 · Cited by 46 · see citing works
Genome-wide quantitative trait loci mapping of the human cerebrospinal fluid proteome
Sasayama, D., Hattori, K., Ogawa, S., Yokota, Y., Matsumura, R., Teraishi, T., Hori, H., Ota, M., Yoshida, S., & Kunugi, H. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw366 · Cited by 43 · see citing works
The use of multiplex platforms for absolute and relative protein quantification of clinical material
Christiansson, L., Mustjoki, S., Simonsson, B., Olsson-Strömberg, U., Loskog, A. S. I., & Mangsbo, S. M. (2014) · EuPA Open Proteomics · doi:10.1016/j.euprot.2014.02.002 · Cited by 34 · see citing works
Initiative, A. D. N., Maxwell, T. J., Corcoran, C., Del‐Aguila, J. L., Budde, J., Deming, Y. K., Cruchaga, C., Goate, A., & Kauwe, J. S. K. (2018) · Alzheimer s Research & Therapy · doi:10.1186/s13195-018-0410-y · Cited by 22 · see citing works
Solomon, T., Lapek, J. D., Jensen, S. B., Greenwald, W. W., Hindberg, K., Matsui, H., Latysheva, N., Braekken, S. K., Gonzalez, D. J., Frazer, K. A., et al. (2018) · Circulation: Genomic and Precision Medicine · doi:10.1161/circgen.118.002170 · Cited by 22 · see citing works
Elhady, M., Youness, E. R., Gafar, H. S., Abdel Aziz, A., & Mostafa, R. S. I. (2018) · Neurological Sciences · doi:10.1007/s10072-018-3448-5 · Cited by 19 · see citing works
Fleitas, C., Marfull-Oromí, P., Chauhan, D., del Toro, D., Peguera, B., Zammou, B., Rocandio, D., Klein, R., Espinet, C., & Egea, J. (2021) · The Journal of Neuroscience · doi:10.1523/jneurosci.0380-20.2021 · Cited by 18 · see citing works
Edsbagge, M., Andreasson, U., Ambarki, K., Wikkelsø, C., Eklund, A., Blennow, K., Zetterberg, H., & Tullberg, M. (2017) · Journal of Alzheimer's Disease · doi:10.3233/jad-161257 · Cited by 17 · see citing works
Self-citationvan Waalwijk van Doorn, L. J. C., Gispert, J. D., Kuiperij, H. B., Claassen, J. A. H. R., Arighi, A., Baldeiras, I., Blennow, K., Bozzali, M., Castelo-Branco, M., Cavedo, E., et al. (2017) · Journal of Alzheimer’s Disease · doi:10.3233/jad-160668 · Cited by 13 · see citing works
Self-citationTrait Loci Mapping and CSF Proteome
Sasayama, D., Hattori, K., & Kunugi, H. (2019) · Methods in Molecular Biology · doi:10.1007/978-1-4939-9706-0_24 · Cited by 1 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Zhao, J. H., Stacey, D., Eriksson, N., Macdonald-Dunlop, E., Hedman, Å. K., Kalnapenkis, A., Enroth, S., Cozzetto, D., Digby-Bell, J. L., Marten, J., et al. (2023) · Nature Immunology · doi:10.1038/s41590-023-01588-w · Cited by 768 · see citing works
Self-citationLarge-scale plasma proteomics comparisons through genetics and disease associations
Eldjarn, G. H., Ferkingstad, E., Lund, S. H., Helgason, H., Magnusson, O. T., Gunnarsdottir, K., Olafsdottir, T. A., Halldorsson, B. V., Olason, P. I., Zink, F., et al. (2023) · Nature · doi:10.1038/s41586-023-06563-x · Cited by 583 · see citing works
Western, D., Timsina, J., Wang, L., Wang, C., Yang, C., Phillips, B., Wang, Y., Liu, M., Ali, M., Beric, A., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01972-8 · Cited by 111 · see citing works
Guo, Y. X., Chen, S.-D., You, J., Huang, S.-Y., Chen, Y., Zhang, Y., Wang, L., He, X., Deng, Y., Zhang, Y.-R., et al. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01924-6 · Cited by 65 · see citing works
Karlsson, L., Vogel, J. W., Arvidsson, I., Åström, K., Janelidze, S., Blennow, K., Palmqvist, S., Stomrud, E., Mattsson, N., & Hansson, O. (2024) · Nature Communications · doi:10.1038/s41467-024-47971-5 · Cited by 62 · see citing works
Self-citationPromises and Challenges of populational Proteomics in Health and Disease
Sun, B. B., Suhre, K., & Gibson, B. W. (2024) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2024.100786 · Cited by 57 · see citing works
Wang, C., Yang, C., Western, D., Ali, M., Wang, Y., Phuah, C., Budde, J., Wang, L., Gorijala, P., Timsina, J., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01973-7 · Cited by 51 · see citing works
Identification of cerebral spinal fluid protein biomarkers in Niemann-Pick disease, type C1
Campbell, K. S., Cawley, N. X., Luke, R., Scott, K. E. J., Johnson, N., Farhat, N. Y., Alexander, D. M., Wassif, C. A., Li, W., Cologna, S. M., et al. (2023) · Biomarker Research · doi:10.1186/s40364-023-00448-x · Cited by 27 · see citing works
Genetic architectures of cerebral ventricles and their overlap with neuropsychiatric traits
Ge, Y., Wu, B., Zhang, Y., Chen, S.-D., Zhang, Y.-R., Kang, J., Deng, Y., Ou, Y., He, X., Zhao, Y., et al. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01722-6 · Cited by 28 · see citing works
Mendelian randomization identifies proteins involved in neurodegenerative diseases
Belbasis, L., Morris, S., van Duijn, C. M., Bennett, D., & Walters, R. G. (2025) · Brain · doi:10.1093/brain/awaf018 · Cited by 29 · see citing works
Therriault, J., Woo, M. S., Salvadó, G., Gobom, J., Karikari, T. K., Janelidze, S., Servaes, S., Rahmouni, N., Tissot, C., Ashton, N. J., et al. (2024) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00689-2 · Cited by 24 · see citing works
Self-citationWang, S., Xi, J., Zhang, M., & Wang, J. (2025) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2024.139394 · Cited by 18 · see citing works
Zhan, H., Cammann, D., Cummings, J. L., Dong, X., & Chen, J. (2025) · Journal of Translational Medicine · doi:10.1186/s12967-025-06317-5 · Cited by 17 · see citing works
Song, J., Qin, Y., Wang, L., Quan, W., Xu, J., Li, J., & Chen, J. (2024) · Scientific Reports · doi:10.1038/s41598-024-53287-7 · Cited by 12 · see citing works
Olink® Explore for High-Throughput Protein Biomarker Discovery in Cerebrospinal Fluid
Boluda-Navarro, M. (2025) · Methods in molecular biology · doi:10.1007/978-1-0716-4462-1_12 · Cited by 10 · see citing works
Saaoud, F., Liu, L., Xu, K., Lu, Y., Shao, Y., Issa, M., Jiang, X., Wang, X., Liu, X., Autieri, M. V., et al. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251329583 · Cited by 11 · see citing works
Yang, C., Gorijala, P., Timsina, J., Wang, L., Liu, M., Wang, C., Brock, W., Wang, Y., Urano, F., Sung, Y. J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-62463-w · Cited by 13 · see citing works
Evaluation of the landscape of pharmacodynamic biomarkers in Niemann-Pick Disease Type C (NPC)
Stern, S., Crisamore, K., Schuck, R. N., & Pacanowski, M. A. (2024) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-024-03233-7 · Cited by 8 · see citing works
Mapping the Cerebrospinal Fluid Proteome in Bipolar Disorder
Göteson, A., Holmén‐Larsson, J., Celik, H., Pelanis, A., Sellgren, C. M., Sparding, T., Pålsson, E., Zetterberg, H., Blennow, K., Jönsson, L., et al. (2025) · Biological Psychiatry · doi:10.1016/j.biopsych.2025.01.007 · Cited by 9 · see citing works
Self-citationSu, Z., & Wan, Q. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1342912 · Cited by 6 · see citing works
Bergström, S., Mravinacová, S., Lindberg, O. E., Zettergren, A., Westman, E., Wahlund, L., Blennow, K., Zetterberg, H., Kern, S., Skoog, I. G., et al. (2024) · Clinical Proteomics · doi:10.1186/s12014-024-09517-1 · Cited by 5 · see citing works
Self-citationYuan, Y.-H., Wang, S., Lian, P.-P., Yu, Z.-H., Gao, X.-T., Duan, Y.-J., Mao, L., & Zhou, Y.-W. (2025) · European Journal of Pharmacology · doi:10.1016/j.ejphar.2025.178297 · Cited by 4 · see citing works
Chaar, D., Li, Z., Shang, L., Ratliff, S. M., Mosley, T. H., Kardia, S. L. R., Zhao, W., Zhou, X., & Smith, J. A. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26062443 · Cited by 5 · see citing works
Sex-aware causal inference assessment of the immune system in complex neurodegenerative diseases
Lona‐Durazo, F., Ross, B., Pilon, M., Greicius, M. D., Dubé, M., Belloy, M. E., McLaughlin, R. L., & Taliun, S. A. G. (2025) · Brain · doi:10.1093/brain/awaf474 · Cited by 4 · see citing works
Connecting dementia risk loci to the CSF proteome identifies pathophysiological leads for dementia
Reus, L. M., Jansen, I. E., Tijms, B. M., Visser, P. J., Tesi, N., van der Lee, S. J., Vermunt, L., Peeters, C. F. W., Groot, L. A. D., Hok‐A‐Hin, Y. S., et al. (2024) · Brain · doi:10.1093/brain/awae090 · Cited by 5 · see citing works
Zhang, J., Zhang, X., Xiao, B., Ouyang, J., Wang, P., & Peng, X. (2024) · Neurogenetics · doi:10.1007/s10048-024-00792-6 · Cited by 4 · see citing works
Genetic insights into drug targets for alzheimer’s disease: integrative multi-omics analysis
Liu, X., Chen, J., Zhou, S., & Lin, J. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01901-9 · Cited by 3 · see citing works
Understanding Neurodegenerative Diseases From the −Omics Perspective: Lessons Learnt
Ibáñez, L., Pottier, C. P., Beric, A., Western, D., Ali, M., & Cruchaga, C. (2026) · Annals of Neurology · doi:10.1002/ana.78170 · Cited by 4 · see citing works
Michopoulou, S. K., Prosser, A. M. J., Dickson, J. C., Guy, M., Teeling, J. L., & Kipps, C. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230726 · Cited by 3 · see citing works
Yang, N., Shi, L., Xu, P., Ren, F., Li, C., & Qi, X. (2024) · Experimental Gerontology · doi:10.1016/j.exger.2024.112538 · Cited by 1 · see citing works
Proteome-wide association study identifies novel Alzheimer's disease-associated proteins
Sun, L., Wei, G., Ji, F., Ding, Y., Fan, J., Xu, Y., He, C., Zhou, Y., Liu, Z., Sun, Z., et al. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251409352 · Cited by 1 · see citing works
Liu, J.-J., Chen, Z., Yang, Q., Lin, H., Wang, S.-Y., Li, M., Wang, T.-G., Zhao, Z.-Y., Xu, M., Chen, Y.-H., et al. (2026) · Communications Medicine · doi:10.1038/s43856-026-01379-y · Cited by 1 · see citing works
Genetic evidence supports therapeutic modulation of progranulin levels in Alzheimer’s Disease
Robins, C., Eicher, J. D., Liu, J., Lo, Y., Richardson, T. G., Western, D., Davitte, J., Cruchaga, C., Initiative, A. D. N., Kumar, U., et al. (2026) · Molecular Neurodegeneration Advances · doi:10.1186/s44477-025-00011-y · Cited by 1 · see citing works
Proteogenomics in human populations.
Zhai, R.-R., Mälarstig, A., & Shen, X. (2026) · Nature reviews genetics · doi:10.1038/s41576-026-00998-4 · Cited by 1 · see citing works
Self-citationXiong, Y., Yang, X., & Jie, J. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.120047 · Cited by 1 · see citing works
Geng, J., Chen, L., Yang, C.-S., Ruan, X., Hu, S., Chen, J., & Wu, Z. (2023) · medRxiv · doi:10.1101/2023.11.22.23298887 · Cited by 1 · see citing works
A Mendelian randomization study identifies proteins involved in neurodegenerative diseasesPreprint
Belbasis, L., Morris, S., van Duijn, C. M., Bennett, D., & Walters, R. G. (2024) · medRxiv · doi:10.1101/2024.02.24.24303314 · Cited by 1 · see citing works
Cruchaga, C., Yang, C., Gorijala, P., Timsina, J., Wang, L., Liu, M., Wang, C., Brock, W., Wang, Y., & Sung, Y. J. (2024) · Research Square · doi:10.21203/rs.3.rs-3617016/v1 · Cited by 1 · see citing works
Shen, J., Huang, Y., Wu, M., Yan, M., Sun, J., Chen, H., Xu, X., Song, P., Yao, P., Xu, Q., et al. (2025) · medRxiv · doi:10.1101/2025.01.14.25320538 · Cited by 1 · see citing works
CSF proteogenomics implicates novel proteins and humoral immunity in Alzheimer’s disease riskPreprint
Wingo, A. P., Liu, Y., Mei, Z. L., Wang, M., Vattathil, S., Gerasimov, E. S., Shantaraman, A., Wu, F., Duong, D. M., Fox, E. J., et al. (2025) · medRxiv · doi:10.1101/2025.09.21.25336297 · Cited by 1 · see citing works
Harpe, R. D. L., Zagkos, L., Gill, D., Cronjé, H. T., & Karhunen, V. (2024) · Biomedicines · doi:10.3390/biomedicines12020327
Hyde, M., Cunningham, M. L., Chai, X., Hu, H. A., Lu, C. S., & Vasanthakumar, A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.11.648439
Stern, S., Crisamore, K., Schuck, R. N., & Pacanowski, M. A. (2024) · Figshare · doi:10.6084/m9.figshare.26384701
Therriault, J., Woo, M. S., Salvadó, G., Gobom, J., Karikari, T. K., Janelidze, S., Servaes, S., Rahmouni, N., Tissot, C., Ashton, N. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26664625
Self-citationStern, S., Crisamore, K., Schuck, R. N., & Pacanowski, M. A. (2024) · Figshare · doi:10.6084/m9.figshare.26384650
Therriault, J., Woo, M. S., Salvadó, G., Gobom, J., Karikari, T. K., Janelidze, S., Servaes, S., Rahmouni, N., Tissot, C., Ashton, N. J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26664619
Self-citationIntegrative multi-omics implicates a CTSB/ITIH-ECM axis in autism spectrum disorder
Wang, G., Zhu, G., Hongyan, L., Wu, L., Zhang, Z., Pang, P., Si, S., & Yang, G. (2026) · Neurobiology of Disease · doi:10.1016/j.nbd.2026.107402 · Cited by 1 · see citing works
Liu, Y., Yi, M., Wei, H., Gu, X., & Liao, W. (2026) · Autoimmunity Reviews · doi:10.1016/j.autrev.2026.104148
Tansey, M. G., Bozeat, S., Ackerman, P., Atri, A., Barnum, C. J., Brundin, P., de Carvalho, C. M. A., Fleisher, A., Graf, A., Head, E., et al. (2026) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.70287
CSF proteomic quantitative trait loci mapping reveals genetic insights into Alzheimer’s disease
Reus, L. M., Jiang, C., Vilor‐Tejedor, N., Boltz, T. A., Yigit, A., Gobom, J., Vos, S. J. B., Blennow, K., Zetterberg, H., Martinez-Lage, P., et al. (2026) · Molecular Neurodegeneration Advances · doi:10.1186/s44477-026-00048-7
Self-citationWu, Z., Ghag, S. A., Shihab, M. H. I., Vasoya, A. P., Sharma, V., Hickman, J. P., Wang, Y., Huang, X., & Huang, M. (2026) · Proteomes · doi:10.3390/proteomes14030049
Zhang, Y., Huang, E., & Lin, N. (2026) · International Journal of Genomics · doi:10.1155/ijog/2340381
Yang, R. T., & Yuan, Y. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.10.05.756343
Research Progress of Low-Intensity Pulsed Ultrasound in Parkinson's Disease
Peng, W., Yang, Y., Wang, J., & 王大明 (2026) · Ultrasound in Medicine & Biology · doi:10.1016/j.ultrasmedbio.2026.09.028
Hyde, M., Cunningham, M. L., Chai, X., Peng, M., Hu, H. A., Lu, C., & Vasanthakumar, A. (2026) · BMC Biotechnology · doi:10.1186/s12896-026-01144-y
- Authors
- Hansson, O., Kumar, A., Janelidze, S., Stomrud, E., Insel, P. S., Blennow, K., Zetterberg, H., Fauman, E., Hedman, Å. K., Nagle, M. W., Whelan, C. D., Baird, D., Mälarstig, A., & Mattsson‐Carlgren, N.
- Affiliations
- Lund University (SE)
- University of California, San Francisco (US)
- Sahlgrenska University Hospital (SE)
- Pfizer (United States) (US)
- Karolinska Institutet (SE)
- Eisai (United States) (US)
- Biogen (United States) (US)
- Corresponding author
- Hansson, Oskar
- ORCID
- Venue
- EMBO Molecular Medicine
- Published
- 2022-12-12
- Volume
- 15
- Issue
- 1
- Pages
- e16359-e16359
- ISSN
- 1757-4676 (ISSN-L)
- 1757-4684
- PMC
- PMC9832827
- OpenAlex
- W4311205850
- Cited by
- 56
- References
- 58
- Citations by year
- 2026: 13 · 2025: 16 · 2024: 20 · 2023: 6 · 2022: 1
- FWCI
- 6.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- EMBO Molecular Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- Alzheimer Drug Discovery Foundation (RDAPB‐201809‐2016615)
- Erling‐Persson Family Foundation
- European Research Council (681712)
- European Union Joint Program for Neurodegenerative Disorders (JPND2021‐00694)
- European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska‐Curie grant agreement (860197)
- Hjärnfonden (FO2017‐0243, FO2019‐0228)
- Knut and Alice Wallenberg Foundation (2017‐0383, WCMM 2019)
- Olav Thon Foundation
- Region Skåne (WCMM 2019)
- Regionalt Forskningsstöd (2020‐0314)
- Stiftelsen för Gamla Tjänarinnor
- Stiftelsen Gamla Tjänarinnor (2019‐00845)
- Strategic Research Area MultiPark
- Swedish Alzheimer Foundation (AF‐939932, AF‐930655, AF‐968453, AF‐742881)
- Swedish Research Council (2018‐02532)
- Swedish State Support for Clinical Research (ALFGBG‐720931)
- Swedish state under the agreement between the Swedish government and the County Councils, the ALF‐agreement (ALFGBG‐715986)
- the AD Strategic Fund and the Alzheimer's Association (ADSF‐21‐831376‐C)
- the Alzheimer Drug Discovery Foundation (201809‐2016862)
- the Alzheimer's Association 2021 Zenith Award (ZEN‐21‐848495)
- The Bundy Academy
- the European Union Joint Program for Neurodegenerative Disorders (JPND2019‐466‐236)
- the Konung Gustaf V:s och Drottning Victorias Frimurarestiftelse
- the Marianne and Marcus Wallenberg foundation (2015.0125)
- The Medical Faculty at Lund University (WCMM 2019)
- the National Institute of Health (1R01AG068398‐01)
- The Parkinson foundation of Sweden (1280/20)
- the Skåne University Hospital Foundation (2020‐O000028)
- the Swedish Brain Foundation (FO2021‐0293, FO2019‐0029, FO2020‐0275)
- the Swedish federal government under the ALF agreement (2018‐Projekt0279, 2018‐Projekt0054)
- UK Dementia Research Institute at UCL
- Vetenskapsrådet (2021‐02219, 2016‐00906, 2017‐00915)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Cerebrospinal fluid and hydrocephalus
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Keywords
- cerebrospinal fluid protein, protein quantitative trait loci, Alzheimer's disease, preclinical Alzheimer's disease, amyotrophic lateral sclerosis, Parkinson's disease, apolipoprotein E, CD33, gene regulatory networks, MMP-10, CD38, GPNMB, ADAM15, CSF proteome, plasma proteins, Mendelian randomization
- MeSH terms
- Alzheimer Disease, Humans, Membrane Glycoproteins, Membrane Proteins, Parkinson Disease, Biomarkers, Antigens, CD, Quantitative Trait Loci, Proteomics, ADAM Proteins, Matrix Metalloproteinase 10, Sialic Acid Binding Immunoglobulin-like Lectins
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-11-01.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-11-01.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review