Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity

Abstract We identified genetic subtypes of type 2 diabetes (T2D) by analyzing genetic data from diverse groups, including non-European populations. We implemented soft clustering with 650 T2D-associated genetic variants, capturing known and novel T2D subtypes with distinct cardiometabolic trait associations. The twelve genetic clusters were distinctively enriched for single-cell regulatory regions. Polygenic scores derived from the clusters differed in distribution between ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a BMI of 30 kg/m2 in the European subpopulation and 24.2 (22.9-25.5) kg/m2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg/m2 in the East Asian group, explaining about 75% of the difference in BMI thresholds. Thus, these multi-ancestry T2D genetic subtypes encompass a broader range of biological mechanisms and help explain ancestry-associated differences in T2D risk profiles..

Medienart:

Preprint

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

ResearchSquare.com - (2024) vom: 06. März Zur Gesamtaufnahme - year:2024

Sprache:

Englisch

Beteiligte Personen:

Udler, Miriam [VerfasserIn]
Smith, Kirk [VerfasserIn]
Deutsch, Aaron [VerfasserIn]
McGrail, Caroyln [VerfasserIn]
Kim, Hyunkyung [VerfasserIn]
Hsu, Sarah [VerfasserIn]
Mandla, Ravi [VerfasserIn]
Schroeder, Philip [VerfasserIn]
Westerman, Kenneth [VerfasserIn]
Szczerbinski, Lukasz [VerfasserIn]
Majarian, Timothy [VerfasserIn]
Kaur, Varinderpal [VerfasserIn]
Williamson, Alice [VerfasserIn]
Claussnitzer, Melina [VerfasserIn]
Florez, Jose [VerfasserIn]
Manning, Alisa [VerfasserIn]
Mercader, Josep [VerfasserIn]
Gaulton, Kyle [VerfasserIn]

Links:

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Themen:

570
Biology

doi:

10.21203/rs.3.rs-3399145/v1

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XRA041106458