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Polygenic scores of diabetes-related traits in subgroups of type 2 diabetes in India: a cohort study

Yajnik, Chittaranjan S. ; Wagh, Rucha ; Kunte, Pooja ; Asplund, Olof LU ; Ahlqvist, Emma LU ; Bhat, Dattatrey ; Shukla, Sharvari R. and Prasad, Rashmi B. LU (2023) In The Lancet Regional Health - Southeast Asia 14.
Abstract
Background
A machine-learning approach identified five subgroups of diabetes in Europeans which included severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD) with partially distinct genetic aetiologies. We previously validated four of the non-autoimmune subgroups in people with young-onset type 2 diabetes (T2D) from the Indian WellGen study. Here, we aimed to apply European-derived centroids and genetic risk scores (GRSs) to the unselected (for age) WellGen to test their applicability and investigate the genetic aetiology of the Indian T2D subgroups.

Methods
We applied European derived... (More)
Background
A machine-learning approach identified five subgroups of diabetes in Europeans which included severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD) with partially distinct genetic aetiologies. We previously validated four of the non-autoimmune subgroups in people with young-onset type 2 diabetes (T2D) from the Indian WellGen study. Here, we aimed to apply European-derived centroids and genetic risk scores (GRSs) to the unselected (for age) WellGen to test their applicability and investigate the genetic aetiology of the Indian T2D subgroups.

Methods
We applied European derived centroids and GRSs to T2D participants of Indian ancestry (WellGen, n = 2217, 821 genotyped) and compared them with normal glucose tolerant controls (Pune Maternal Nutrition Study, n = 461).

Findings
SIDD was the predominant subgroup followed by MOD, whereas SIRD and MARD were less frequent. Weighted-GRS for T2D, obesity and lipid-related traits associated with T2D. We replicated some of the previous associations of GRS for T2D, insulin secretion, and BMI with SIDD and MOD. Unique to Indian subgroups was the association of GRS for (a) proinsulin with MOD and MARD, (b) liver-lipids with SIDD, SIRD and MOD, and (c) opposite effect of beta-cell GRS with SIDD and MARD, obesity GRS with MARD compared to Europeans. Genetic variants of fucosyltransferases were associated with T2D and MOD in Indians but not Europeans.

Interpretation
The similarities emphasise the applicability of some of the European-derived GRSs to T2D and its subgroups in India while the differences highlight the need for large-scale studies to identify aetiologies in diverse ancestries. The data provide robust evidence for genetically distinct aetiologies for the T2D subgroups and at least partly mirror those seen in Europeans. (Less)
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author
; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
The Lancet Regional Health - Southeast Asia
volume
14
article number
100182
publisher
Elsevier
external identifiers
  • pmid:37492423
  • scopus:85163563969
ISSN
2772-3682
DOI
10.1016/j.lansea.2023.100182
language
English
LU publication?
yes
id
eceb8218-7a8f-4923-81a3-cabe6b8ef312
date added to LUP
2023-05-03 10:41:47
date last changed
2024-05-03 22:24:48
@article{eceb8218-7a8f-4923-81a3-cabe6b8ef312,
  abstract     = {{Background<br/>A machine-learning approach identified five subgroups of diabetes in Europeans which included severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD) with partially distinct genetic aetiologies. We previously validated four of the non-autoimmune subgroups in people with young-onset type 2 diabetes (T2D) from the Indian WellGen study. Here, we aimed to apply European-derived centroids and genetic risk scores (GRSs) to the unselected (for age) WellGen to test their applicability and investigate the genetic aetiology of the Indian T2D subgroups.<br/><br/>Methods<br/>We applied European derived centroids and GRSs to T2D participants of Indian ancestry (WellGen, n = 2217, 821 genotyped) and compared them with normal glucose tolerant controls (Pune Maternal Nutrition Study, n = 461).<br/><br/>Findings<br/>SIDD was the predominant subgroup followed by MOD, whereas SIRD and MARD were less frequent. Weighted-GRS for T2D, obesity and lipid-related traits associated with T2D. We replicated some of the previous associations of GRS for T2D, insulin secretion, and BMI with SIDD and MOD. Unique to Indian subgroups was the association of GRS for (a) proinsulin with MOD and MARD, (b) liver-lipids with SIDD, SIRD and MOD, and (c) opposite effect of beta-cell GRS with SIDD and MARD, obesity GRS with MARD compared to Europeans. Genetic variants of fucosyltransferases were associated with T2D and MOD in Indians but not Europeans.<br/><br/>Interpretation<br/>The similarities emphasise the applicability of some of the European-derived GRSs to T2D and its subgroups in India while the differences highlight the need for large-scale studies to identify aetiologies in diverse ancestries. The data provide robust evidence for genetically distinct aetiologies for the T2D subgroups and at least partly mirror those seen in Europeans.}},
  author       = {{Yajnik, Chittaranjan S. and Wagh, Rucha and Kunte, Pooja and Asplund, Olof and Ahlqvist, Emma and Bhat, Dattatrey and Shukla, Sharvari R. and Prasad, Rashmi B.}},
  issn         = {{2772-3682}},
  language     = {{eng}},
  month        = {{05}},
  publisher    = {{Elsevier}},
  series       = {{The Lancet Regional Health - Southeast Asia}},
  title        = {{Polygenic scores of diabetes-related traits in subgroups of type 2 diabetes in India: a cohort study}},
  url          = {{http://dx.doi.org/10.1016/j.lansea.2023.100182}},
  doi          = {{10.1016/j.lansea.2023.100182}},
  volume       = {{14}},
  year         = {{2023}},
}