Cross-sectional, interventional, and causal investigation of insulin sensitivity using plasma proteomics in diverse populations Article Swipe
Pik Fang Kho
,
Neil Wary
,
Daniela Zanetti
,
Fahim Abbasi
,
Joshua W. Knowles
,
Daniel J. Panyard
,
Katie Watson
,
Laurel Stell
,
Laura C. Lazzeroni
,
Stefan Gustafsson
,
Lars Lind
,
John R. Petrie
,
Themistocles L. Assimes
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.11.09.24317011
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.11.09.24317011
Background We previously reported significant correlations between a direct measure of insulin sensitivity (IS) and blood levels of proteins measured using the Proximity Extension Assay (PEA) in two European cohorts. However, protein correlations with IS within non-European populations, in response to short-term interventions that improve IS, and any causal associations with IS have not yet been established. Methods We measured 1,470 proteins using the PEA in the plasma of 1,015 research participants at Stanford University who underwent one or more direct measures of IS. Association analyses were carried out with multivariable linear regression within and across Stanford subgroups and within each of the two European cohorts. Association statistics were also meta-analyzed after transformation and harmonization of the two direct measures of IS. Lastly, we performed genome-wide association studies of IS and used genetic instruments of plasma proteins from the UK Biobank to identify candidate causal proteins for IS through Mendelian Randomization (MR) analysis. Results In age and sex adjusted model, 810 proteins were associated with baseline IS among 652 self-reported European participants in the Stanford cohort at a false discovery rate (FDR) < 0.05. Effect sizes for these proteins were highly correlated with those observed in 122 South Asian, 92 East Asian, 85 Hispanic, and 52 Black/African American persons (r= 0.68 to 0.83, all P≤4.3×10 -113 ). Meta-analysis of the full Stanford cohort with the two European cohorts (N=2,945) yielded 247 significant protein associations (FDR < 0.05), with 75 remaining significant after further adjustment for body mass index. In a subset of Stanford participants undergoing insulin sensitizing interventions (N=53 taking thiazolidinediones, N=66 with weight loss), 79.6% of protein level changes were directionally consistent with the respective baseline association (observed/expected p=6.7x10 -16 ). MR analyses identified eight candidate causal proteins for IS, among which were SELE and ASGR1, proteins with established drug targets currently under investigation. Conclusion Plasma proteins measured using the PEA provide a robust signature for IS across diverse populations and after short-term insulin sensitizing interventions highlighting their potential value as universal biomarkers of insulin resistance. A small subset of markers provided insights into potential causal molecular mechanisms and therapeutic targets. Highlights Insulin sensitivity-related plasma proteins are consistent across diverse populations. Protein changes from interventions align with baseline, aiding insulin sensitivity tracking. SELE and ASGR1 are potential targets for insulin sensitivity.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2024.11.09.24317011
- https://www.medrxiv.org/content/medrxiv/early/2024/11/12/2024.11.09.24317011.full.pdf
- OA Status
- green
- Cited By
- 2
- References
- 61
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404281934
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4404281934Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2024.11.09.24317011Digital Object Identifier
- Title
-
Cross-sectional, interventional, and causal investigation of insulin sensitivity using plasma proteomics in diverse populationsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-12Full publication date if available
- Authors
-
Pik Fang Kho, Neil Wary, Daniela Zanetti, Fahim Abbasi, Joshua W. Knowles, Daniel J. Panyard, Katie Watson, Laurel Stell, Laura C. Lazzeroni, Stefan Gustafsson, Lars Lind, John R. Petrie, Themistocles L. AssimesList of authors in order
- Landing page
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https://doi.org/10.1101/2024.11.09.24317011Publisher landing page
- PDF URL
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https://www.medrxiv.org/content/medrxiv/early/2024/11/12/2024.11.09.24317011.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.medrxiv.org/content/medrxiv/early/2024/11/12/2024.11.09.24317011.full.pdfDirect OA link when available
- Concepts
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Insulin sensitivity, Sensitivity (control systems), Insulin, Proteomics, Plasma levels, Internal medicine, Medicine, Computational biology, Insulin resistance, Chemistry, Biology, Engineering, Biochemistry, Gene, Electronic engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
- References (count)
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61Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(MR) | 152 |
| abstract_inverted_index.-113 | 216 |
| abstract_inverted_index.0.68 | 211 |
| abstract_inverted_index.East | 201 |
| abstract_inverted_index.N=66 | 262 |
| abstract_inverted_index.SELE | 295, 374 |
| abstract_inverted_index.also | 110 |
| abstract_inverted_index.been | 56 |
| abstract_inverted_index.body | 246 |
| abstract_inverted_index.drug | 301 |
| abstract_inverted_index.each | 101 |
| abstract_inverted_index.from | 138, 365 |
| abstract_inverted_index.full | 221 |
| abstract_inverted_index.have | 53 |
| abstract_inverted_index.into | 345 |
| abstract_inverted_index.mass | 247 |
| abstract_inverted_index.more | 80 |
| abstract_inverted_index.rate | 181 |
| abstract_inverted_index.that | 44 |
| abstract_inverted_index.used | 132 |
| abstract_inverted_index.were | 87, 109, 163, 190, 271, 294 |
| abstract_inverted_index.with | 34, 51, 90, 165, 193, 224, 238, 263, 274, 299, 368 |
| abstract_inverted_index.(FDR) | 182 |
| abstract_inverted_index.(N=53 | 259 |
| abstract_inverted_index.(PEA) | 26 |
| abstract_inverted_index.0.05. | 184 |
| abstract_inverted_index.0.83, | 213 |
| abstract_inverted_index.1,015 | 70 |
| abstract_inverted_index.1,470 | 61 |
| abstract_inverted_index.79.6% | 266 |
| abstract_inverted_index.ASGR1 | 376 |
| abstract_inverted_index.Assay | 25 |
| abstract_inverted_index.South | 198 |
| abstract_inverted_index.after | 112, 242, 323 |
| abstract_inverted_index.align | 367 |
| abstract_inverted_index.among | 168, 292 |
| abstract_inverted_index.blood | 16 |
| abstract_inverted_index.eight | 286 |
| abstract_inverted_index.false | 179 |
| abstract_inverted_index.level | 269 |
| abstract_inverted_index.sizes | 186 |
| abstract_inverted_index.small | 339 |
| abstract_inverted_index.their | 329 |
| abstract_inverted_index.these | 188 |
| abstract_inverted_index.those | 194 |
| abstract_inverted_index.under | 304 |
| abstract_inverted_index.using | 21, 63, 310 |
| abstract_inverted_index.value | 331 |
| abstract_inverted_index.which | 293 |
| abstract_inverted_index.0.05), | 237 |
| abstract_inverted_index.ASGR1, | 297 |
| abstract_inverted_index.Asian, | 199, 202 |
| abstract_inverted_index.Effect | 185 |
| abstract_inverted_index.Plasma | 307 |
| abstract_inverted_index.across | 96, 319, 360 |
| abstract_inverted_index.aiding | 370 |
| abstract_inverted_index.causal | 49, 145, 288, 347 |
| abstract_inverted_index.cohort | 176, 223 |
| abstract_inverted_index.direct | 9, 81, 119 |
| abstract_inverted_index.highly | 191 |
| abstract_inverted_index.index. | 248 |
| abstract_inverted_index.levels | 17 |
| abstract_inverted_index.linear | 92 |
| abstract_inverted_index.loss), | 265 |
| abstract_inverted_index.model, | 160 |
| abstract_inverted_index.plasma | 68, 136, 356 |
| abstract_inverted_index.robust | 315 |
| abstract_inverted_index.subset | 251, 340 |
| abstract_inverted_index.taking | 260 |
| abstract_inverted_index.weight | 264 |
| abstract_inverted_index.within | 36, 94, 100 |
| abstract_inverted_index.Biobank | 141 |
| abstract_inverted_index.Insulin | 354 |
| abstract_inverted_index.Lastly, | 123 |
| abstract_inverted_index.Methods | 58 |
| abstract_inverted_index.Protein | 363 |
| abstract_inverted_index.Results | 154 |
| abstract_inverted_index.between | 7 |
| abstract_inverted_index.carried | 88 |
| abstract_inverted_index.changes | 270, 364 |
| abstract_inverted_index.cohorts | 228 |
| abstract_inverted_index.diverse | 320, 361 |
| abstract_inverted_index.further | 243 |
| abstract_inverted_index.genetic | 133 |
| abstract_inverted_index.improve | 45 |
| abstract_inverted_index.insulin | 12, 256, 325, 336, 371, 381 |
| abstract_inverted_index.markers | 342 |
| abstract_inverted_index.measure | 10 |
| abstract_inverted_index.persons | 209 |
| abstract_inverted_index.protein | 32, 233, 268 |
| abstract_inverted_index.provide | 313 |
| abstract_inverted_index.studies | 128 |
| abstract_inverted_index.targets | 302, 379 |
| abstract_inverted_index.through | 149 |
| abstract_inverted_index.yielded | 230 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.American | 208 |
| abstract_inverted_index.European | 29, 105, 171, 227 |
| abstract_inverted_index.However, | 31 |
| abstract_inverted_index.Stanford | 74, 97, 175, 222, 253 |
| abstract_inverted_index.adjusted | 159 |
| abstract_inverted_index.analyses | 86, 284 |
| abstract_inverted_index.baseline | 166, 277 |
| abstract_inverted_index.cohorts. | 30, 106 |
| abstract_inverted_index.identify | 143 |
| abstract_inverted_index.insights | 344 |
| abstract_inverted_index.measured | 20, 60, 309 |
| abstract_inverted_index.measures | 82, 120 |
| abstract_inverted_index.observed | 195 |
| abstract_inverted_index.p=6.7x10 | 280 |
| abstract_inverted_index.proteins | 19, 62, 137, 146, 162, 189, 289, 298, 308, 357 |
| abstract_inverted_index.provided | 343 |
| abstract_inverted_index.reported | 4 |
| abstract_inverted_index.research | 71 |
| abstract_inverted_index.response | 40 |
| abstract_inverted_index.targets. | 352 |
| abstract_inverted_index.(N=2,945) | 229 |
| abstract_inverted_index.Extension | 24 |
| abstract_inverted_index.Hispanic, | 204 |
| abstract_inverted_index.Mendelian | 150 |
| abstract_inverted_index.Proximity | 23 |
| abstract_inverted_index.analysis. | 153 |
| abstract_inverted_index.baseline, | 369 |
| abstract_inverted_index.candidate | 144, 287 |
| abstract_inverted_index.currently | 303 |
| abstract_inverted_index.discovery | 180 |
| abstract_inverted_index.molecular | 348 |
| abstract_inverted_index.performed | 125 |
| abstract_inverted_index.potential | 330, 346, 378 |
| abstract_inverted_index.remaining | 240 |
| abstract_inverted_index.signature | 316 |
| abstract_inverted_index.subgroups | 98 |
| abstract_inverted_index.tracking. | 373 |
| abstract_inverted_index.underwent | 77 |
| abstract_inverted_index.universal | 333 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.Conclusion | 306 |
| abstract_inverted_index.Highlights | 353 |
| abstract_inverted_index.University | 75 |
| abstract_inverted_index.adjustment | 244 |
| abstract_inverted_index.associated | 164 |
| abstract_inverted_index.biomarkers | 334 |
| abstract_inverted_index.consistent | 273, 359 |
| abstract_inverted_index.correlated | 192 |
| abstract_inverted_index.identified | 285 |
| abstract_inverted_index.mechanisms | 349 |
| abstract_inverted_index.previously | 3 |
| abstract_inverted_index.regression | 93 |
| abstract_inverted_index.respective | 276 |
| abstract_inverted_index.short-term | 42, 324 |
| abstract_inverted_index.statistics | 108 |
| abstract_inverted_index.undergoing | 255 |
| abstract_inverted_index.Association | 85, 107 |
| abstract_inverted_index.P≤4.3×10 | 215 |
| abstract_inverted_index.association | 127, 278 |
| abstract_inverted_index.established | 300 |
| abstract_inverted_index.genome-wide | 126 |
| abstract_inverted_index.instruments | 134 |
| abstract_inverted_index.populations | 321 |
| abstract_inverted_index.resistance. | 337 |
| abstract_inverted_index.sensitivity | 13, 372 |
| abstract_inverted_index.sensitizing | 257, 326 |
| abstract_inverted_index.significant | 5, 232, 241 |
| abstract_inverted_index.therapeutic | 351 |
| abstract_inverted_index.associations | 50, 234 |
| abstract_inverted_index.correlations | 6, 33 |
| abstract_inverted_index.established. | 57 |
| abstract_inverted_index.highlighting | 328 |
| abstract_inverted_index.non-European | 37 |
| abstract_inverted_index.participants | 72, 172, 254 |
| abstract_inverted_index.populations, | 38 |
| abstract_inverted_index.populations. | 362 |
| abstract_inverted_index.sensitivity. | 382 |
| abstract_inverted_index.Black/African | 207 |
| abstract_inverted_index.Meta-analysis | 218 |
| abstract_inverted_index.Randomization | 151 |
| abstract_inverted_index.directionally | 272 |
| abstract_inverted_index.harmonization | 115 |
| abstract_inverted_index.interventions | 43, 258, 327, 366 |
| abstract_inverted_index.meta-analyzed | 111 |
| abstract_inverted_index.multivariable | 91 |
| abstract_inverted_index.self-reported | 170 |
| abstract_inverted_index.investigation. | 305 |
| abstract_inverted_index.transformation | 113 |
| abstract_inverted_index.(observed/expected | 279 |
| abstract_inverted_index.sensitivity-related | 355 |
| abstract_inverted_index.thiazolidinediones, | 261 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5008652100 |
| countries_distinct_count | 4 |
| institutions_distinct_count | 13 |
| corresponding_institution_ids | https://openalex.org/I204866599, https://openalex.org/I25790992, https://openalex.org/I97018004 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.5899999737739563 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.8489303 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |