<p>Correct classification of type 1 (T1D) and type 2 diabetes (T2D) is challenging due to overlapping clinical features and the increasingly early onset of T2D, particularly in South Asians. Polygenic risk scores (PRSs) for T1D and T2D have been shown to work relatively well in South Asians, despite being derived from largely European-ancestry samples. Here we used PRSs to investigate the rate of potential misclassification of diabetes amongst British Bangladeshis and Pakistanis. Using linked health records from the Genes &amp; Health cohort (n = 38,344) we defined two reference groups meeting stringent diagnostic criteria: 31 T1D cases, 1842 T2D cases, and after excluding these, two further groups: 839 insulin-treated diabetic individuals with ambiguous features and 5174 non-diabetic controls. Combining these with 307 confirmed T1D cases and 307 controls from India, we calculated ancestry-corrected PRSs for T1D and T2D, with which we estimated the proportion of T1D cases within the ambiguous group at ~ 6%, dropping to ~ 4.5% within the subset who had T2D codes in their health records (and are thus most likely to have been misclassified). We saw no significant association between the T1D or T2D PRS and BMI at diagnosis, time to insulin, or the presence of T1D or T2D diagnostic codes amongst the T2D or ambiguous cases, suggesting that these clinical features are not particularly helpful for aiding diagnosis in ambiguous cases. Our results emphasise that robust identification of T1D cases and appropriate clinical care may require routine measurement of diabetes autoantibodies and C-peptide.</p>

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Investigating misclassification of type 1 diabetes in a population-based cohort of British Pakistanis and Bangladeshis using polygenic risk scores

  • Timing Liu,
  • Alagu Sankareswaran,
  • Gordon Paterson,
  • Shaheen Akhtar,
  • Ana Angel,
  • Omar Asgar,
  • Samina Ashraf,
  • Saeed Bidi,
  • Gerome Breen,
  • James Broster,
  • Raymond Chung,
  • David Collier,
  • Charles J. Curtis,
  • Shabana Chaudhary,
  • Grainne Colligan,
  • Panos Deloukas,
  • Ceri Durham,
  • Faiza Durrani,
  • Fabiola Eto,
  • Sarah Finer,
  • Karen A. Hunt,
  • Matt Hurles,
  • Shapna Hussain,
  • Kamrul Islam,
  • Vivek Iyer,
  • Benjamin M. Jacobs,
  • Georgios Kalantzis,
  • Ahsan Khan,
  • Claudia Langenberg,
  • Cath Lavery,
  • Sang Hyuck Lee,
  • Daniel MacArthur,
  • Eamonn Maher,
  • Daniel Malawsky,
  • Sidra Malik,
  • Hilary Martin,
  • Dan Mason,
  • Rohini Mathur,
  • Mohammed Bodrul Mazid,
  • John McDermott,
  • Caroline Morton,
  • Bill Newman,
  • Vladimir Ovchinnikov,
  • Elizabeth Owor,
  • Iaroslav Popov,
  • Asma Qureshi,
  • Mehru Raza,
  • Jessry Russell,
  • Stuart Rison,
  • Nishat Safa,
  • Annum Salman,
  • Miriam Samuel,
  • Moneeza K. Siddiqui,
  • Michael Simpson,
  • John Solly,
  • Marie Spreckley,
  • Daniel Stow,
  • Michael Taylor,
  • Richard C. Trembath,
  • Karen Tricker,
  • Klaudia Walter,
  • Jan Whalley,
  • Caroline Winckley,
  • Suzanne Wood,
  • John Wright,
  • Sabina Yasmin,
  • Ishevanhu Zengeya,
  • Julia Zöllner,
  • Diane P. Fraser,
  • Sam Hodgson,
  • Qin Qin Huang,
  • Teng Hiang Heng,
  • Meera Ladwa,
  • Nick Thomas,
  • David A. van Heel,
  • Michael N. Weedon,
  • Chittaranjan S. Yajnik,
  • Richard A. Oram,
  • Giriraj R. Chandak,
  • Hilary C. Martin,
  • Sarah Finer

摘要

Correct classification of type 1 (T1D) and type 2 diabetes (T2D) is challenging due to overlapping clinical features and the increasingly early onset of T2D, particularly in South Asians. Polygenic risk scores (PRSs) for T1D and T2D have been shown to work relatively well in South Asians, despite being derived from largely European-ancestry samples. Here we used PRSs to investigate the rate of potential misclassification of diabetes amongst British Bangladeshis and Pakistanis. Using linked health records from the Genes & Health cohort (n = 38,344) we defined two reference groups meeting stringent diagnostic criteria: 31 T1D cases, 1842 T2D cases, and after excluding these, two further groups: 839 insulin-treated diabetic individuals with ambiguous features and 5174 non-diabetic controls. Combining these with 307 confirmed T1D cases and 307 controls from India, we calculated ancestry-corrected PRSs for T1D and T2D, with which we estimated the proportion of T1D cases within the ambiguous group at ~ 6%, dropping to ~ 4.5% within the subset who had T2D codes in their health records (and are thus most likely to have been misclassified). We saw no significant association between the T1D or T2D PRS and BMI at diagnosis, time to insulin, or the presence of T1D or T2D diagnostic codes amongst the T2D or ambiguous cases, suggesting that these clinical features are not particularly helpful for aiding diagnosis in ambiguous cases. Our results emphasise that robust identification of T1D cases and appropriate clinical care may require routine measurement of diabetes autoantibodies and C-peptide.